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・ Social media analytics
・ Social media and political communication in the United States
・ Social media and suicide
・ Social media and television
・ Social media and the Arab Spring
・ Social media as a public utility
・ Social media bubble
・ Social Media Examiner
・ Social Media Giving Day
・ Social media in the fashion industry
・ Social media intelligence
・ Social Media Language Learning
・ Social media management system
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Social media mining
・ Social media newsroom
・ Social media optimization
・ Social media surgery
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・ Social Media Working Group Act of 2014
・ Social medicine
・ Social messaging
・ Social microcosm
・ Social mirror theory
・ Social mobile application
・ Social Mobilisation Network (SMNet)
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・ Social model of disability


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Social media mining : ウィキペディア英語版
Social media mining
Social Media Mining is the process of representing, analyzing, and extracting actionable patterns from social media data. Social Media Mining, introduces basic concepts and principal algorithms suitable for investigating massive social media data; it discusses theories and methodologies from different disciplines such as computer science, data mining, machine learning, social network analysis, network science, sociology, ethnography, statistics, optimization, and mathematics. It encompasses the tools to formally represent, measure, model, and mine meaningful patterns from large-scale social media data.
==Background==

As defined by Kaplan and Haenlein, social media is the “group of internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of user-generated content.” There are many categories of social media including, but not limited to, social networking (Facebook or LinkedIn), microblogging (Twitter), photo sharing (Flickr, Photobucket, or Picasa), news aggregation (Google reader, StumbleUpon, or Feedburner), video sharing (YouTube, MetaCafe), livecasting (Ustream or Twitch.tv), virtual worlds (Kaneva), social gaming (World ofWarcraft), social search (Google, Bing, or Ask.com), and instant messaging (Google Talk, Skype, or Yahoo! messenger).
The first social media site was introduced by GeoCities in 1994, which allowed users to create their own homepages. The first social networking site, SixDegree.com, was introduced in 1997. Since then, many other social media sites have been introduced, each providing service to millions of people. These individuals form a virtual world in which individuals (social atoms), entities (content, sites, etc.) and interactions (between individuals, between entities, between individuals and entities) coexist. Social norms and human behavior govern this virtual world. By understanding these social norms and models of human behavior and combining them with the observations and measurements of this virtual world, one can systematically analyze and mine social media. Social media mining is the process of representing, analyzing, and extracting meaningful patterns from data in social media, resulting from social interactions. It is an interdisciplinary field encompassing techniques from computer science, data mining, machine learning, social network analysis, network science, sociology, ethnography, statistics, optimization, and mathematics. Social media mining faces grand challenges such as the big data paradox, obtaining sufficient samples, the noise removal fallacy, and evaluation dilemma.
Social media mining represents the virtual world of social media in a computable way, measures it, and designs models that can help us understand its interactions. In addition, social media mining provides necessary tools to mine this world for interesting patterns, analyze information diffusion, study influence and homophily, provide effective recommendations, and analyze novel social behavior in social media.

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