Optimization of social media engagement

Optimization of social media connection

The technology described in this article is related to social media, and particularly to methods and systems for optimizing social media engagement.

Social media sites are becoming more and more popular by having the ability to connect users and groups in a cooperative manner. Social media services explore opportunities for advanced communications and also act as an advanced content sharing mechanism. Examples include not only social network services (SNSs) such as MYSPACE and Facebook (FACEBOOK), but also telecommunication operation services such as messaging, picture sharing, person-to-person and conference calls, and even telecommunications services such as Twitter ( TWITTER's microblogging service.

Thousands of users actively use the services provided through such social media sites, and explore new trends in communications and content sharing that has been atypical in the past. For example, TWITTER has more than 100 million active users and generates more than 250 million tweets every day (20% of which contain links). Therefore, social media sites such as TWITTER provide an attractive channel for online marketing and sales.

The overwhelming amount of information available from social media sites creates challenges in the effective use of such information in marketing strategies. Traditional social media analysis has focused on brand monitoring and reputation management on such social media sites. It is expected to provide methods and systems for exploring methods to drive acquisition through social media sites.

Therefore, in view of the above-mentioned problems, the purpose of the present invention is to introduce a selection concept in a simplified form. For further description, please refer to the detailed description below. The purpose of the content of the present invention is not to identify the key features or essential features of the subject matter requested in the scope of the patent application, nor to use it as an auxiliary means to determine the scope of the subject matter requested in the scope of the patent application.

The techniques described in this article often involve methods for optimizing social media connectivity. In some embodiments, such a method may include identifying search engine optimized keywords for at least one webpage, and identifying social media responses that refer to one or more search engine optimized keywords. The method may further include recommending materials related to search engine optimization keywords that are referenced in social media responses used for social media connections.

In other embodiments, such a method may include collecting content from a plurality of webpages by crawling at least one website; searching for content collected from a plurality of webpages to identify references to at least one keyword; analyzing the content to determine the relationship between the plurality of webpages A frequency of at least one related reference of at least one keyword, the related reference system is generated through social media users, and at least one report is generated for display, and the report contains content-based information.

The techniques described in this article often involve systems for optimizing social media. For example, such a system includes: a deep indexing engine configured to crawl multiple web pages and identify social media responses located on the multiple web pages; an analysis module configured to analyze social media responses to identify social media responses And create at least one report and a report module based on the reference of at least one keyword to generate at least one report displayed to a user. The report contains information based on social media response analysis.

These and other aspects of the specific embodiments of the present invention will become more completely clear from the following description and the scope of the attached patent application.

In the following detailed description, reference will be made in conjunction with the accompanying drawings which are part of the present invention. In these drawings, similar symbols usually indicate similar elements, unless there are other instructions in the text. The illustrated embodiments described in the following description, drawings and claims are not meant to be limited thereto. Those skilled in the art should realize that other embodiments can be used and other changes can be made without departing from the spirit and scope of the present invention disclosed in the scope of the patent application attached to the present invention. Those skilled in the art should realize that the aspects of the present invention as described in the text and shown in the drawings can be set up, replaced, combined, separated and designed in a variety of different configurations, all of which can be obviously considered.

With the widespread use of social media and the growth of integration with the daily lives of Internet users, companies and individuals (such as "entities") are realizing the benefits of using social media in their marketing strategies. As an entity turns to social media for help, it may hopefully be able to identify when a social media response involves the content on the entity's webpage. It is more expected to provide the ability to use content from physical web pages to provide connections in social media responses.

Therefore, the embodiments disclosed herein generally involve computing systems and computing processes used in methods of optimizing social media connectivity by tracking and linking in social media responses. By linking up in social media responses, an entity can gain greater visibility of brand names. Moreover, connection in social media responses can lead to an increase in the traffic of a physical homepage and a better page ranking of the physical webpage.

Reference will now be made to the drawings, in which the same structures will be provided with the same reference numerals. It can be understood that the drawings are schematic diagrams and principle diagrams of some embodiments of the present invention, but they are not a limitation of the present invention, nor are they necessarily drawn to scale.

"Figure 1A" is an embodiment of a social media optimization system 100a that can include a network 102. In some embodiments, the network 102 can be used to interconnect various parts of the system 100a, such as a web server 106, a deep indexing engine 108, a correlator 104, and a social media optimization module 112 . It will be appreciated that while these elements are shown separately, these elements can be combined as required. In addition, when one of each element is described, the system 100a may optionally include any number of each element.

The network 102 may include the Internet. The Internet includes a global Internet path formed by logical and physical connections between multiple wide area networks and/or local area networks, and may optionally include the World Wide Web ("web pages"). One of the Internet hypertext archives to visit. In addition or alternatively, the network 102 includes one or more cellular radio frequency (RF) networks and/or one or more wired and/or wireless networks, such as but not limited to, 802.xx network, Bluetooth Access point, wireless access point, Internet Protocol (IP)-based network, or the like. The network 102 may also include servers that can interface one type of network to another type of network.

The web server 106 may include any system capable of storing and transmitting a web page to a user. The web server 106 may provide an entry to a web page of a website that will be analyzed to improve social media optimization. For example, the web server 106 may include a computing system that is responsible for receiving requests from clients (such as the user agent of a web browser) and serving them with hypertext transfer protocol (HTTP) responses and optional data content, optional data content Can contain hypertext markup language (HTML) files and link objects for display to users. Additionally or alternatively, the web server 106 may include the ability to record some detailed information about user requests and service responses to a log file.

The website can contain any number of web pages. Reference to the collection of various web pages can be referred to as traffic. It should be noted that the term webpage used in this article refers to any online publication, including domains, subdomains, web posts, uniform resource identifiers ("URIs"), uniform resource locators ("URLs"), images, and videos Or other content and non-permanent announcements such as e-mail and chat, unless otherwise specified.

In some embodiments, the deep index engine 108 may be configured to crawl web pages accessed by the web server 106 to obtain external information. As used herein, the terms "crawl" and "crawling" can refer to the collection of the contents of multiple files or websites (such as webpages) on the network 102, and the contents can be searched. In particular, the deep indexing engine 108 can be configured to crawl web pages and analyze data related to the crawling. This data includes on-page information for each web page and back link data (such as back link URL, anchor text, etc.) Wait). The deep index engine 108 can be configured to crawl web pages via the Internet and/or via a wireless network. Social media is often accessed through a wireless network using a mobile device (such as a mobile phone, a personal assistant (PDA), a tablet computer, etc.). The deep indexing engine 108 can use an algorithm or a software mechanism (such as a crawler) to crawl files or websites on the network 102 to request content.

Therefore, web pages crawled by the deep indexing engine 108 through the wireless network can provide user-specific and/or location-specific information. According to one of the embodiments, more details of the deep indexing engine 108 are described in the pending U.S. patent application. The U.S. patent application serial number is 12/436,704 and is titled "Collection and Scoring Online REFERENCES)", the application date is May 6, 2009. The full text of the application can be combined for reference. The functions described in this article can be applied to a website to optimize the web pages of a website.

According to one of the embodiments, more details of the correlator 104 are described in the pending U.S. patent application. The U.S. patent application serial number is 12/574,069, the application date is October 6, 2009, and the title is "With external reference Correlative web page access and conversion (CORRELATING WEB PAGE VISITS AND CONVERSIONS WITH EXTERNAL REFERENCES)", the full text of the application can be combined as a reference. The functions described in this article can be applied to a website to optimize the web pages of a website.

The correlator 104 or other components can be configured to collect web page analysis data from the web page. Web analytics data can be used to estimate the cost, value, or both associated with one or more search engine optimization (SEO) opportunities or social media optimization opportunities. Examples of web analytics data that can be collected include multiple visitors, web browsing, conversions (such as purchases), and the like or any combination thereof.

The social media optimization module 112 is configured to track, identify, and analyze social media responses and coordination, and perform web page analysis of a website as described in this article, and then make recommendations to improve social media interaction and increase the exposure of entities Therefore, the SEO of the website is improved. The social media optimization module 112 can access social media responses generated by a user device (such as a computer or a mobile phone) during the communication on the network 112. More details of the social media optimization module 112 are described here.

"Figure 1B" is another embodiment of a social media optimization system 100b. As shown in the figure, the network 102 operatively connects the social media optimization module 112 and a website computing system 128. The social media optimization module 112 includes a computing system 120 configured to perform social media optimization analysis and generate recommendations as described herein. The SEO computing system 120 may include sub-modules for performing special functions. The computing system 120 may belong to and include an analysis module 122, a judgment module 124, and a report module 126.

The website computing system 128 may include a website database 129 that includes SEO data from a physical webpage 132 of a physical website 130. The physical website 130 is a website of an entity that is about to be implemented for social media optimization. The website database 129 further includes social media web pages 142 from a social media website 140 of one entity. The social media website 140 is any type of social media. For example, social media can include collaborative projects (e.g. Wikipedia), blogs and micro-blogs (e.g. Twitter TWITTER), content communities (e.g. video sites), social networking sites (e.g. Facebook), virtual game worlds (e.g. Such as World of Warcraft) and virtual social worlds (such as Second Life), in other types of social media, and can take many different forms, including online forums, web blogs, micro blogs, social blogs, wikis, Podcasts, photos or pictures, videos, ratings, social bookmarks and others. The social media web page 142 may include any type of digital content of social media from the social media website 140.

For example, if the social media website 140 is a micro-blog or a micro-blog website such as TWITTER, the social media web page 142 may contain a single micropost and a micro-blog account with a collection of user micro-posts. One of the users homepage, or any other digital content containing microposts.

A micropost can include a message or a post published on a website or distributed to a specific group of subscribers, and subscribers can browse them via the Internet via, for example, a computer or a mobile device. Such a micropost can be, for example, a status update, a comment, a post (for example, a website address) or a so-called "check-in" in a specific location via social media. exist<img file="TW201239642A_D0001.tif" />Such a micropost on social network services is often referred to as a "tweet<img file="TW201239642A_D0002.tif" />", the user can copy and forward another tweet, which is often referred to as a "reposted tweet". A micropost can contain one or more so-called "hybrid tags", where the "#" sign is used to mark a<img file="TW201239642A_D0003.tif" />Words or topics in. A microblog can also be a response to an original tweet, such as a reply to another tweet, and it is often represented by a "@" symbol and a user name.

In order for customers to find direct revenue, tweets can be used to drive reference traffic and conversions from Twitter. However, this may be challenging for customers because it may require customers to identify high-value opportunities and respond very quickly to relevant and competitive tweets and content.

As another example, if the social media website 140 is a social networking site such as Facebook, the social media web page 142 may be a networked webpage of a user, a post of a user, a comment, or any other digital content related to the social network. content. Additionally or alternatively, the website computing system 128 may include a second website database, and the physical web pages 132 and the social media web pages 142 may be stored in separate databases. It should be understood that the data from the physical web page 132 and the social media web page 142 can be stored in any configuration without departing from the embodiments described herein.

The website computing system 128 accesses the physical website 130 and the social media website 140 through a web server such as the web server 106 in "Figure 1A", and can obtain information from the physical web page 132 and the social media web page 142. Moreover, the data from the physical webpage 132 and the social media webpage 142 can be collected by crawling the physical webpage 132 and the social media webpage 142. In some embodiments, the physical webpage 132 and the social media webpage 142 can be crawled using the deep indexing engine 108 of "Figure 1A", for example. In some embodiments, the physical web page 132 and the social media web page 142 can be crawled using a different mechanism.

In a predetermined aggregation period, information can be obtained from the physical web page 132 and the social media web page 142. For example, the predetermined aggregation period may be a time period such as one or more hours, days, or weeks. As a non-limiting example, data can be obtained on a single day or a single week.

In some embodiments, the website computing system 128 can implement a keyword count, in which each occurrence of a keyword is counted to determine the keyword count. The keyword volume may include a count or number of precise and/or phrase matching occurrences of one of the keywords in a social media response such as a tweet. The appearance of keywords can be classified according to the type of social media response in which they appear.

In the embodiment where the social media response is obtained from social media (such as TWITTER), each occurrence of a keyword can be classified as one of the responses posted by another (such as reposting a tweet), being reposted by another, or an initial A response (e.g. a tweet) posted in response (e.g. a tweet). The occurrence of keywords marked by a specific user-defined topic (for example, through the "#" number) or by a user name (for example, through the "@" number) can be counted as one of the number of response metrics.

One or more keyword trends can be determined based on the amount of keywords. The keyword trend strength can be calculated from a percentage difference between the amount of keywords and an average amount of keywords that have passed a predetermined period of time (for example, an aggregation period). As a non-limiting example, the aggregation period may be one day, and the keyword trend strength may include a percentage deviation from an average amount determined after another predetermined time period (for example, 7 days). As another non-limiting example, the aggregation period may be one week, and the keyword trend strength may include a percentage deviation from an average amount determined after another predetermined time period (for example, 4 weeks).

In addition, the website computing module 128 can filter data from the physical web page 132 and the social media web page 142. The data can be filtered based on any relevant criteria such as a large number of web pages or a period of time. As a non-limiting example, the sample size can be selected to include a predetermined number of web pages, and the website computing module 128 can be configured to obtain information from a sample of a physical web page 132 and/or social media web page 142 according to the relevant sample size . Therefore, instead of obtaining data from each web page that contains SEO keywords entered through a third party, the data can be filtered to include a specific number or percentage of web pages, or to include one or more sites of interest. Samples from physical web pages 132 and social media web pages 142 can be used to determine the frequency of one of the SEO keywords. Using filtered data, the frequency of SEO keywords appearing in web pages (such as physical web pages 132 and social media web pages 142) can be estimated. For example, if the sample size is 50% of the web pages, the number of SEO keyword references appearing in the web pages obtained from the sample can be doubled to provide an estimate of the actual number of SEO keyword references. If the data obtained from the sample indicates that one of the keyword references is low in number, or there is no keyword reference, a larger sample size can be selected or the filter can be removed to ensure the accuracy of the estimation.

As another non-limiting example, data can be filtered based on a predetermined time period. You can select a time period, and you can determine the number of SEO keyword references that appear on the web page during this time period. Therefore, the frequency of SEO keyword reference in this predetermined time period can be determined.

The filtering criteria can be dynamically changed based on the selected information. For example, as additional information is collected and analyzed, the group of pages or SEO keywords that have been crawled after this period of time can be modified. Furthermore, the filtering data can be used to estimate the frequency of SEO keyword references appearing on web pages, determine the frequency of SEO keyword references appearing on web pages within a predetermined period of time, and/or determine the frequency of SEO keyword references appearing on a predetermined set of web pages One frequency of keyword reference. Because companies can be charged a fee for each of the SEO keywords they choose, it is useful to filter data in estimating one of the potential costs associated with such services provided to such companies.

Referring again to the SEO calculation module 120, the analysis module 122 in the SEO calculation module 120 may be configured to analyze the physical web page 132 and the social media web page 142 to obtain data from the physical web page 132 and the social media web page 142. The analysis module 122 may include one or more algorithms for analyzing the physical web page 132 and the social media web page 142. In some embodiments, the analysis module 122 can analyze online data, source code, or any other data of the physical webpage 132 to identify SEO keywords. The SEO keywords can include any brand name of the entity or other words related to the entity or Word strings, product names produced by entities, product categories, related search terms, general topics, and other words or word strings used in SEO.

In some embodiments, the analysis module 122 can analyze the on-page data, source code, or any other data of the social media webpage 142 on the physical webpage 132 to identify social media responses. The social media response can be any information that can be read by other users of the social media website 140 that is placed on the social media web page 142 by a user of the social media website 140. For example, in some embodiments, social media responses may include posts, comments, or both on a social networking website. In some embodiments, the social media response may include posts, comments, or both on a blog or a mini-blog. It should be understood that the above mentioned are only some examples of different types of social media responses, and the scope of social media responses used in this article should not be limited by these examples.

Additionally or alternatively, after the analysis module 122 identifies the social media response located on the social media web page 142, the analysis module 122 can use one or more algorithms to further analyze the social media for one or more words, phrases, and other data. The media responded. For example, in some embodiments, the analysis module 122 may analyze social media responses to identify SEO keywords identified by the analysis module 122 in the social media web page 132.

Additionally or alternatively, the analysis module 122 can analyze the on-page data, source code, or both of the social media web page 142 and/or the social media website 140 to identify information about a specific user of the social media website 140. The identified information may include a user's social media participation and content provided or discussed by the user. The user's social media participation may include how often the user participates in the social media, such as the number of social media responses generated by the user. In addition or alternatively, the user's social media participation can include how many other users of social media follow, browse, comment, refer to, help or otherwise respond to the social media responses generated by the user. By using high-performance keywords (for example, having an average volume higher than the reference and/or providing a keyword higher than the average return on investment), the analysis can realize the preparation of recommendations to improve visibility. For example, keyword trend analysis can be used to provide information about social medias valuable keyword trends, and to show how personal web pages are ranked and converted into high-performance keywords, to provide opportunity alerts to use existing content to drive connections To society, and to prioritize which social media opportunity will be the most effective, if tracked. Recommendations may further include determining one or more web pages related to targeted customers identified as interested in specific keywords. For example, customers who are interested in the selected criticality can be identified, and based on the selected keywords, a decision can be made as to which web pages will be the best for locating these target customers. Such webpages can be identified based on an analysis of a ranking obtained from one or more search engines, a number or a type of transmission, conversion, bounce rate, conversion rate, and revenue. As a non-limiting example, recommendations can include web pages that are determined to be ranked higher and/or have a higher than average number of visits or conversions.

Some embodiments further involve analysis and/or generation of analysis involving social media responses and SEO keyword identification. The analysis can be derived from information received or collected from physical web pages 132 and social media web pages 142. Information can also be used for target marketing across platforms. Information can also be used to generate revenue. Information can be used to target specific advertisements to specific customers. In addition, demographic data such as customer demographic data (when provided), device type, content type, and the like can be collected and used to generate analysis.

The information can also be used to determine the value of SEO keywords or physical web pages 132 and social media web pages 142 and/or to rank the value of one of the SEO keywords or physical web pages 132 and social media web pages 142. For example, information indicating that SEO keywords are referenced more frequently in social media responses than other SEO keywords can be used by ranking SEO keywords and/or the relevance of physical pages 132 and social media pages 142Information. Information. More frequently referenced SEO keywords can be ranked higher than other less referenced SEO keywords. The physical webpage 132 and the social media webpage 142 that refer to a specific SEO keyword of interest more frequently than other webpages can be ranked higher than other webpages. Information can also be used, for example, to predict or determine the price point of social media connections.

In another example, the analysis can be used to predict which SEO keywords are more likely to be referenced in social media and/or which web pages are more likely to contain SEO key references.

Analysis can also be used to determine SEO keywords that provide a higher return on investment (ROI). As used herein, the term "return on investment" can refer to the revenue generated from SEO keywords or the popularity of keywords compared to the costs related to the use of SEO keywords.

In addition, one or more web pages with the highest number of SEO keyword references can also be judged. For example, web pages can be categorized in order of the frequency of keywords related to social media. The web pages that contain the highest number of SEO keyword references can be judged, and those web pages can be targeted and optimized. In identifying the most relevant SEO keywords in social media and web pages most relevant to specific SEO keywords, the social media optimization system 100b described herein enables the adjustment of marketing strategies to optimize the use of SEO keywords.

The judgment module 124 can also be configured to judge one or more web pages shared in social media regardless of SEO keywords. Information related to such web pages can be analyzed to determine relevant SEO keywords and to optimize social media responses.

The judgment module 124 can obtain data from the analysis module 122, and use the data to determine which identified social media response contains the identified SEO keywords in the physical web page 132. The decision module 124 may include one or more algorithms for processing the data obtained from the analysis module 122. Additionally or alternatively, the judgment module 124 can judge the frequency of the SEO keywords from the physical website 132 in the identified social media responses, and rank the SEO keywords accordingly. Additionally or alternatively, the determination module 124 may determine whether there is an increase in the use of one or more identified SEO keywords after a period of time.

Additionally or alternatively, the judgment module 124 may judge a ranking of a user of the social media website 140 relative to other users of the social media website 140 in terms of social media participation. For example, for a microblog such as TWITTER, the number of followers, retweets, and a users TWITTER views can be used to rank a user relative to all other users of TWITTER. In addition or alternatively, the judgment module 124 may also use other factors, for example, by using the influence and participation ranking factors generated by other websites or entities to determine the ranking of a user's social media participation. Additionally or alternatively, the judgment module 124 can determine which social media sites 140 users are discussing, providing, viewing, or otherwise having social media responses related to the identified SEO keywords.

The report module 126 can compile information from the analysis module 122, the judgment module 124, or the sum of the two to generate different types of reports, and give recommendations to improve social media optimization. The reporting module 126 can include one or more algorithms that can generate one or more reports and provide one or more recommendations for improving social media optimization.

The decision module 124 can access data from one or more mobile devices via a wireless network to collect information, and generate market information based on location. For example, following the positioning of social media responses or the login/sign-in information provided in social media responses can be analyzed to determine the reference of keywords based on the positioning.

The judgment module 124 can analyze trends related to SEO keywords, such as growth, consumption, and content creation in social media responses and demographic data (such as gender, race, age, interests, education, employment status, and location). The information obtained from such analysis can be provided in, for example, a report, an electronic report, and/or an electronic notification, and can be used to adjust market strategies. Electronic reports can be displayed on a computer screen, downloaded into one or more electronic file formats, or printed on paper, for example.

Such reports generated based on the collected information may include, for example, activity reports, incentive reports, dynamic graphs, and so on. Reports can contain information about users related to web pages, SEO keywords, social media, or social media. As a non-limiting example, such a report may contain a dynamic graph of activities related to SEO keywords or related to web pages containing at least one reference SEO keyword. As another non-limiting example, such a report may include an analysis of one of the referenced web pages according to SEO keywords (such as web pages with the highest number of occurrences). As yet another non-limiting example, such a report may contain demographic information about users related to SEO keyword references.

For example, an all keyword report can be generated, allowing users to quickly observe what keywords and web pages can most effectively drive revenue. Such keywords may be those with the highest number of references in social media or those with the largest increase in references within a predetermined period of time. All keyword reports can additionally provide information about keywords in a set of multiple keyword groups (such as multiple product categories) that are increasing in social media responses. Such webpages may be those that contain the highest number of keywords with reference to one or more selected keywords or may be those whose frequency of keywords that are selected with reference is increasing most rapidly. As a non-limiting example, the report can provide information related to keywords and web pages contained in a social media response, such as a tweet sent by a Twitter user, to drive revenue. For example, reports can provide information about the most powerful trending keywords and the high-value pages and opportunities involving those keywords. The all keywords report may include, for example, a stacked histogram showing the volume of all keywords by keyword trend strength.

The report can be customized according to the customer's specifications. For example, the report can be customized to include keywords with a deviation of 0% or less from the average, keywords that tend to be higher than 0% but less than 50% above the average, and the deviation from the average tends to be higher than 50 % But less than 100% keywords, and/or keywords that tend to 100% or more above the average.

As a non-limiting example, the report can be an electronic report that includes a web-based graphical user interface or a screen where data can be viewed. The electronic report can contain one or more buttons linked to a map of each trend strength category. When any button is selected, the keyword information can be filtered. For example, the data can be filtered or sorted to show only the keywords in the particular trend category described by the button.

The report can contain any number of areas, and each area can involve keywords or social media. As a non-limiting example, a region can include keywords with the highest number (keyword rankings), web pages with the highest number of keyword references (such as top ranking webpages), organic search revenue for keywords in a predetermined period of time, and / Or a percentage change in the keyword volume. A trend report on one of the top ranking webpages containing each keyword and one or more other webpages containing the keyword can be generated.

The report may include a function that can display information for a specific date and/or time. For example, a specific date in the past can be selected and data from that date can correspond to that date.

The report can also include an option for outputting data in another format such as a text file, a comma separated value (CSV) file or any other type of file. The output data can include all or part of the data shown in the electronic report. The output data may additionally include, for example, several visits, several web page views, sessions, and/or customization in a predetermined period of time. Reports can also be configured as one or more at a glance views or so-called "dashboards." Keywords linked between social media responses and webpages can be used to generate specific recommendations to utilize these webpages and drive connections and revenue on social media. Such recommendations will be tied to keywords and web pages.

The tools provided to customers for optimizing social media results and campaigns can maximize the connection, transmission and conversion of customers through social media such as Twitter.

"Figure 2" is an embodiment of a method 200 for increasing social media connections. The method 200 may be executed in, for example, the SEO system 100a in "Figure 1A" or the SEO system 100b in "Figure 1B". The method 200 may include in block 210 identifying one or more SEO keywords from a web page of an entity. In some embodiments, identifying one or more SEO keywords from a webpage of an entity may include the website of the crawling entity, obtaining SEO data from the website, and identifying the SEO keywords. SEO keywords can include any brand name of the entity or other words or word strings related to the entity, product names produced by the entity, product categories, related search keywords, common topics, and other words or words used in SEO string.

The method 200 may further include identifying social media responses from social media web pages that refer to SEO keywords in block 220. In some embodiments, identifying social media responses from social media webpages may include crawling social media webpages, obtaining SEO data from the website, and analyzing social responses that are located on social media webpages to refer to previously identified SEO keywords. In some embodiments, SEO keywords that are often referred to in social media responses can be annotated. Additionally or alternatively, the frequency with which SEO keywords are referenced in social media responses can be judged and tracked to create a moving average of the number of references. If the number of social media responses referring to a specific SEO keyword is higher or lower than the moving average of the reference number used for the SEO keyword or keyword string, the SEO keyword or keyword string can be annotated.

In some embodiments, the method 200 may further include identifying social media participants with higher than average social media participation. Social media participants with higher than average social media participation can be considered as influential participation. These social media participants can be identified based on one or more factors. Factors can include the number of followers of social media participants, the number of social media responses, and other factors.

In some embodiments, the method 200 may further include identifying a specific social media participant who has provided input to the social media response regarding the reference SEO keyword.

The method 200 may further include the recommended material in block 230 that refers to the web page containing the SEO keywords referenced in the social media response and is used for social media connection. Cohesion in social media can include contributing to social media by generating social media responses, distributing social media responses, or some other contribution. In some embodiments, materials related to all SEO keywords referenced in social media responses can be used to link in social media. Additionally or alternatively, only materials related to SEO keywords that are above the moving average of the number of social media responses to the reference SEO keywords can be used to link in social media. Additionally or alternatively, only materials related to SEO keywords that are below the moving average of the number of social media responses to the reference SEO keywords are used to link in social media. Additionally or alternatively, only materials related to one of the SEO keywords with the highest number of references in the social media response or a predetermined percentage of one of the SEO keywords with the highest number of references are used to link in the social media. In some embodiments, materials related to SEO keywords are materials from a webpage where the SEO keywords are derived.

Additionally or alternatively, the method 200 may include recommending social media participants who have provided social media responses with reference to SEO keywords to link with materials related to SEO keywords. Social media participants can be connected by sending new social media responses from social media participants, replying to social media responses generated by social media participants, or by connecting social media participants with social media participants. Additionally or alternatively, the method 200 may include recommending social media participants with higher than average social media participation to link materials involving SEO keywords that the social media participants have previously included in their social media responses.

Additionally or alternatively, the method 200 may include recommendations for recommending new or additional content for a webpage of a user that has been identified in a social media response involving one of the SEO keywords.

In some embodiments, the method may further include providing a period of data related to the number of SEO keywords referenced in the social media response. The data can be produced in the form of a report with one or more images, charts, graphs, or other displays. In addition or alternatively, the entity may be provided with information related to social media responses referring to a certain SEO keyword, any SEO keyword, or a combination of SEO keywords after a period of time.

An example of method 200 is shown below. For example, an entity of a shoe store may have a website that displays and provides shoes for sale. Web pages can be crawled, such as the brand of shoes and SEO keywords such as shoes, performance, running, and other words can be identified. Social media pages can also be crawled. For example, all pages of a website Twitter can be crawled, and social media responses such as a tweet can be identified and analyzed to identify SEO keywords in the social media responses. Based on the SEO keywords identified in the social media response, a recommendation can be made to a shoe store to be posted on social media by generating and publishing tweets containing information about shoes such as a sales volume, shoe profit, or other materials .

Some of the embodiments disclosed herein include a computer program product with computer-executed instructions for causing an operating system with a computer program product to execute a computer-executable instruction for improving the SEO of a physical social media webpage. method. The calculation method can be any method described in this text that is executed by a calculation system. The computer program product can be positioned on a computer storage device that can be removed or integrated with the computing system.

Some embodiments include the computing system described herein that can perform this method. Likewise, the computing system may include a storage device with computer-executable instructions for executing the method.

In some embodiments, a computing device such as a computer or a storage device of a computer may include an analysis module, a judgment module, and a report module. The analysis module, the judgment module, and the report module can be configured to perform any of the methods described herein. Similarly, the analysis module, the judgment module, and the report module can be combined into a single module or a single platform.

The computer program product may contain one or more algorithms for executing any method of any request item.

Those skilled in the art will realize that for this and other processes and methods disclosed herein, the functions and methods performed in these processes and methods can be executed in a different order. Moreover, the outlined steps and operations are not only provided as examples, some of the steps and operations may be optional, combined into fewer steps and operations, or if the essence of the disclosed embodiments is not compromised. Expanded to additional steps and operations. It should also be realized that any module or component described herein can perform the function associated with the name of the module or component.

The disclosure of the present invention is not limited to the specific embodiments described in this application, and it is intended to be an illustration of all aspects. It will be obvious to those skilled in the art to make numerous modifications and changes without departing from its spirit and scope. In addition to those listed herein, methods and devices with equivalent functions within the scope of the present disclosure will be apparent to those skilled in the art from the above description. Such modifications and changes are intended to fall within the scope of the attached patent application. The disclosure of the present invention is not limited to the items within the scope of the appended application, but within the full scope equivalent to the rights granted to such items. It can also be understood that the terminology used herein only describes specific embodiments, but is not intended to be limiting.

In an illustrated embodiment, any of the operations, processes, etc. described herein can be executed as computer-readable instructions stored in a computer-readable medium. Computer readable instructions can be executed through a processor of a mobile unit, a network element and/or any other computing device.

There is a slight difference on the left side between the hardware execution and the software execution in the system. The use of software or hardware is usually (but not always, because in certain environments, the choice of hardware and software can become important ) It reflects one of the design choices of cost versus efficiency trade-off. Through the processes and/or systems and/or other technologies described herein, it can be affected (for example, software, hardware, and/or firmware) to have various carriers, and preferred carriers are used in the process and/or system and/or Other technologies will change with the environment. For example, if an implementer decides that speed and accuracy are the most important, the implementer can choose a major hardware and/or firmware carrier; if flexibility is the most important, the implementer can choose a major software implementation; or , Once again as another option, implementers can choose some components of hardware, software and/or firmware.

The above detailed description has stated various embodiments of the present process through the use of block diagrams, flowcharts, and/or examples. Within the scope of such block diagrams, flowcharts, and/or examples, one or more functions and/or operations are included, and those skilled in the art will understand that each in such block diagrams, flowcharts, and/or examples The functions and/or operations can be performed individually and/or selectively through a wide range of hardware, software, firmware, or almost any combination thereof. In some embodiments, several parts of the subject described in this article can be executed via application-specific integrated circuits (ASICs), field programmable logic gate arrays (FPGAs), digital signal processors (DSPs), or other integrated formats . However, those skilled in the art will recognize that certain aspects of the embodiments disclosed herein are accompanied by one or more computer programs running on one or more computers (for example, one or more programs running on one or more computer systems), With one or more programs running on one or more processors (for example, with one or more programs running on one or more microprocessors), with firmware or with almost any combination of them, in the whole or part It can be executed equally in the integrated circuit, and designing the circuit and/or writing code for software and/or firmware will be in the skill of a person skilled in the art according to this disclosure. In addition, those skilled in the art will be pleased that the mechanism of the subject described in this article can be distributed as a program product in various forms, and one of the subjects described in this article describes the application of the signal-bearing medium in the embodiment. Regardless of the special type to actually perform the allocation. Examples of a signal receiving medium include, but are not limited to, the following: such as a floppy disk, a hard disk drive, a compact disc (CD), a digital versatile disc (DVD), a digital tape, a computer storage, etc. Recordable medium, and a transmission medium such as a digital and/or an analog communication medium (for example, a fiber optic cable, a waveguide, a wired communication link, a wireless communication link, etc.).

Those skilled in the art should be aware that it is common in the art to describe devices and/or processes in the form described herein, and then use engineering practices to integrate the described devices and/or processes into a data processing system. That is, at least part of the devices and/or processes described herein can be integrated into a data processing system through a reasonable number of experiments. Those skilled in the art should be aware that a typical data processing system usually includes one or more of the following devices: a system unit housing, a video display device, such as one of volatile and non-volatile memories, Processors such as microprocessors and digital signal processors, computing entities such as operating systems, drivers, graphical user interfaces, and applications, such as one or more interactive devices such as a touch pad or touch screen, and/or include feedback Circuit and control motor control system (ie, feedback for sensing position and/or speed; control motor for moving and/or adjusting parts and/or quantity). A typical data processing system can be implemented using any suitable commercially available components, such as those commonly found in data computing/communication systems and/or network computing/communication systems.

The subject matter disclosed in the text sometimes states that different components are contained in or connected to other different components. It should be understood that the structure described in this way is only exemplary, and in fact many other results can be executed and achieve the same function. In a conceptual sense, any set of components that obtain the same function is effectively "associated" so that the desired function can be obtained. Therefore, the combination of any two components to obtain a specific function can be regarded as "related" to each other, so that the desired function can be obtained, regardless of the structure or the intermediate components. Similarly, any two related components can also be regarded as mutually "operably connected" or "operably coupled" to achieve the desired function, and any two related components can also be regarded as mutually "operable" Operationally can be coupled" to obtain the desired function. Specific examples of operably coupleable include, but are not limited to, physically coupled and/or physically interactive components and/or wirelessly interactable components and/or wirelessly interactable components and/or logically interactable components and/or logically interactable components Function parts.

"Figure 3" shows an example computing device 300 arranged to perform any of the computing methods described herein. In a relatively basic configuration 302, the computing device 300 often includes one or more processors 304 and a system memory 306. A storage bus 308 can be used to communicate between the processor 304 and the system storage 306.

Depending on the desired configuration, the processor 304 may be of any type including but not limited to a microprocessor (μP), a microcontroller (μC), a digital signal processor (DSP), or any combination thereof. The processor 304 may include more than one cache level such as a first level cache 310 and a first level cache 312, a processor core 314, and a register 316. An example processor core 314 may include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP core), or any combination thereof. An example storage controller 318 may also be used with the processor 304, or the storage controller 318 may be an internal part of the processor 304 in some implementations.

Depending on the desired configuration, the system storage 306 may include, but is not limited to, volatile storage (such as random access memory (RAM)), non-volatile storage (such as read-only memory (ROM), flash memory, etc.), or they Any combination of any type. The system storage 306 may include an operating system 320, one or more application programs, and program data 324. The application 322 may include a decision application 326 that is arranged to perform the functions described herein including the functions described in the method described herein. For example, the judgment application 326 may be equivalent to the judgment module 124 in "Figure 1B". The program data 324 may include decision data 328 useful for analyzing social media responses located on social media web pages. In some embodiments, the application program 322 may be arranged to operate the program data 624 on the operating system 320.

The computing device 300 may have additional features or functions, as well as additional interfaces to facilitate communication between the basic configuration 302 and any required devices and interfaces. For example, a bus/interface controller 330 can be used to facilitate communication between the basic configuration 302 and one or more data storage devices 332 via a storage interface bus 334. The data storage device 332 can be a removable storage device 336, a non-removable storage device 338, or a combination of them. Examples of removable storage devices and non-removable storage devices include disk devices such as floppy disk drives and hard disk drives (HDD), optical disk drives such as record (CD) drives or digital versatile disk (DVD) drives , Solid state drives (SSD), and tape drives to name just a few examples. Example computer storage media may include volatile and non-volatile media, removable and non-removable media implemented in any method or technology for information storage such as computer-readable instructions, data structures, program modules, or other data In addition to the media.

The system storage 306, the removable storage device 336, and the non-removable storage device 338 are examples of computer storage media. Computer storage media include but are not limited to RAM, ROM, electrically erasable read-only memory (EEPROM), flash memory or other storage technologies, read-only disc drives (CD-ROM), digital versatile discs (DVD) or other optical discs Storage, cassette tape, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and that can be accessed through the computing device 300. Any such computer storage medium can be part of the computing device 300.

The computing device 300 may also include an interface bus 340 for facilitating communication from various interface devices (such as the output device 342, the peripheral interface 344, and the communication device 346) to the basic configuration 302 via the bus/interface controller 330. The example output device 342 includes a graphics processing unit 348 and an audio processing unit 350. The audio processing unit 350 can be configured to communicate with various external devices such as a display or speaker via one or more audio/video ports 352. The example peripheral interface 344 includes a serial interface controller 354 or a parallel interface controller 356, which can be configured to communicate with input devices such as keyboard, mouse, pen, voice input via one or more input/output ports 358 Devices, touch input devices, etc.) or other peripheral devices (such as printers, scanners, etc.). An example communication device 346 includes a network controller 360, which can be arranged to facilitate communication with one or more other computing devices 362 via a network communication link via one or more communication ports 364.

The network communication link can be an example of a communication medium. Communication media can often be through computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanisms, and can include any information transmission media. A "modulated data signal" can be a signal that has one or more of one or more characteristic settings that are set or changed in such a way that information is encoded in the signal. By way of example but not limitation, the communication media may include wired media such as a wired network or a direct connection, wireless media such as original sound, radio frequency (RF), microwave, infrared (IR), and other wireless media. The term computer-readable media used herein can include both storage media and communication media.

The computing device 300 can be implemented as a mobile phone, a personal assistant (PDA), a personal media player, a wireless webpage monitoring device, a personal headset device, a dedicated device, or a hybrid device containing any of the above functions. A part of a small and portable (or mobile) electronic device. The computing device 300 can be implemented as a personal computer including a laptop configuration and a non-laptop configuration. The computer device 300 can also be any type of network computing device. The computing device 300 may also be an automatic system described herein.

The embodiments described herein may include the use of a special purpose or a general purpose computer with different computer hardware modules or software modules.

Embodiments within the scope of the present invention also include computer-readable media for carrying or executing computer-executable instructions or data structures stored thereon. Such computer-readable media can be any available media that can be accessed through a general-purpose or special-purpose computer. By way of example but not limitation, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, other magnetic storage devices, or may be in the form of computer-executable instructions or data structures. Used to carry and store expected program code values and any other media that can be accessed by a general purpose computer or a special purpose computer. When information is transferred or provided to a computer via a network or another communication connection (hard-wired, wireless, or a combination of circuit or wireless), the computer appropriately treats the connection as a computer-readable medium . Therefore, any such connection is appropriately called a computer-readable medium. The combination of the above should also be included in the scope of computer-readable media.

Computer-executable instructions include, for example, instructions and data that cause a general-purpose computer, special-purpose computer, or special-purpose processing device to perform a certain function or group of functions. Although the subject matter has been described in terms of structural features and/or method operations, it should be understood that the subject matter defined within the scope of the appended application does not necessarily limit the specific features or operations described above. On the contrary, the special features and operations described above are disclosed as an example form of executing the request.

As used herein, the term "module" or "component" can refer to software objects or routines executed in a computing system. The various components, modules, engines, and servers described herein can be executed as targets or processes executed on the computing system (for example, as separate threads). While the system and method described in this article are well executed in software, it is also possible and expected to execute in hardware or a combination of software and hardware. In this description, a "computing entity" can be any computing system defined in this article, or any module or combination of modules that runs a computing system.

Regarding the use of any plural and/or individual words, as suitable for the environment and/or application, those skilled in the art can convert from plural to individual and/or from individual to plural. Various single/plural exchanges can be explained in the text for clarity.

Those skilled in the art should understand that the words generally used in the text and especially in the scope of the attached application (ie, the part of the scope of the attached application) are usually expressed as "open" words (ie, the words "including" Should be interpreted as "including but not limited to", the word "having" should be interpreted as "having at least", and the word "includes" should be interpreted as "including but not limited to" etc.). Those skilled in the art should also understand that if a certain number of reference request items are listed as expected, then such expectation will be clearly listed in the request item, and without such enumeration, this expectation will not exist. For example, as an aid to understanding, the following appended claims may include the use of the introductory phrases "at least one" and "one or more" to introduce the list of claims. However, the use of such phrases should not be construed as implying that the restriction on the introduction of one of the claims listed by the non-qualifying article "a" includes any particular claim listed in such an introduction to an embodiment that includes only one such enumeration, even if When the same claim contains the introduction phrase "one or more" or "at least one" and the non-qualifying article "one" (ie, "one" should be interpreted as meaning "at least one" or "one or more"); The same applies to the qualifying articles used to introduce the claim list. In addition, even if a specific number of listings for the introduction of a claim is explicitly enumerated, those skilled in the art should understand that such enumeration will be interpreted as indicating at least the enumerated number (ie, directly enumerating "two enumerations" without other modifiers , It means at least two enumerations, or two or more enumerations). In addition, in sentences that use a convention similar to "at least one of A, B, and C", generally, such a structure expects those skilled in the art to understand such convention (ie, "Have A, B, and C" "At least one of the systems" will include, but is not limited to, systems with only A, systems with only B, systems with only C, systems with A and B, systems with A and C, systems with B and C Systems, and/or systems with A, B, and C, etc."). In sentences that use a convention similar to "at least one of A, B, or C", generally, such a structure is expected to be understood by those skilled in the art (ie, "has at least one of A, B or C" "One-for-one system" will include, but is not limited to, a system with only A, a system with only B, a system with only C, a system with A and B, a system with A and C, a system with B and C, And/or systems with A, B, and C, etc."). Those skilled in the art should also understand that Any transitional conjunctions and/or phrases representing two or more alternative words, whether in the specification, claims or drawings, should be understood as including one of these words, any or all of these words It's possible. For example, the phrase "A or B" should be understood to include the possibility of "A" or "B" or "A and B".

In addition, in the context of the disclosure of features or aspects described in the Markusson group, those skilled in the art should understand that the disclosure is also described in terms of a single element or a subgroup of elements of the Markusson group.

Those skilled in the art should understand that, for any and all purposes, such as providing a written description, all ranges disclosed in the text also include any and all possible subranges and combinations of subranges. Any listed range can be easily understood as effectively describing and causing the same range to be decomposed into at least equal halves, thirds, quarters, fifths, deciles, etc. As a non-limiting example, each range discussed in the text can be easily decomposed into a low three-segment, a middle three-segment, and a high three-segment. Those skilled in the art should understand that all languages such as "up to", "at least" and the like include enumerated quantities and references to ranges that can be subsequently broken down into sub-ranges as discussed above. Finally, those skilled in the art should understand that a range includes each individual member. Thus, for example, a group with 1-3 batteries means a group with 1 battery, 2 batteries, or 3 batteries. Similarly, a group with 1-5 batteries means a group with 1 battery, 2 batteries, 3 batteries, 4 batteries, 5 batteries, and so on.

Those skilled in the art should realize that without departing from the spirit and scope of the present invention disclosed in the scope of the patent application attached to the present invention, all changes and modifications made are within the scope of the patent protection of the present invention. For the scope of protection defined by the present invention, please refer to the attached scope of patent application.

<p>100a. . . SEO system</p><p>100b. . . SEO system</p><p>102. . . network</p><p>104. . . Correlator</p><p>106. . . Web server</p><p>108. . . Deep indexing engine</p><p>112. . . Social media optimization module</p><p>120. . . SEO computing system</p><p>122. . . Analysis module</p><p>124. . . Judgment module</p><p>126. . . Report module</p><p>128. . . Website computing system</p><p>129. . . Website database</p><p>130. . . Physical website</p><p>132. . . Physical page</p><p>140. . . Social media site</p><p>142. . . Social media pages</p><p>200. . . method</p><p>210. . . Cube</p><p>220. . . Cube</p><p>230. . . Cube</p><p>300. . . Computing device</p><p>302. . . basic configuration</p><p>304. . . processor</p><p>306. . . System memory</p><p>308. . . Storage bus</p><p>310. . . Level 1 cache</p><p>312. . . Secondary cache</p><p>314. . . Processor core</p><p>316. . . register</p><p>318. . . Storage controller</p><p>320. . . System</p><p>322. . . application</p><p>324. . . Program data</p><p>326. . . Judgment App</p><p>328. . . Judgment information</p><p>330. . . Bus/Interface Controller</p><p>332. . . Data storage device</p><p>334. . . Storage interface bus</p><p>336. . . Removable storage device</p><p>338. . . Non-removable storage</p><p>340. . . Interface bus</p><p>342. . . Output device</p><p>344. . . Peripheral interface</p><p>346. . . Communication device</p><p>348. . . Graphics processing unit</p><p>350. . . Audio processing unit</p><p>352. . . Audio/Video port</p><p>354. . . Serial Interface Controller</p><p>356. . . Parallel Interface Controller</p><p>358. . . Input/output port</p><p>360. . . Network controller</p><p>362. . . Computing device</p><p>364. . . Communication port</p>

Figure 1A is an embodiment of a social media connection system according to one of the technologies described in this article;

Figure 1B is another embodiment of a social media connection system according to one of the technologies described herein;

Figure 2 is a flowchart of an embodiment of a method for increasing social media connection according to the technology described herein; and

Figure 3 is an embodiment of a computing system described herein that can execute part of the embodiments.