Social networks analysis

Social networks analysis


Social medias in today’s modern society are counted as one of the most important tools for communication a social interaction. Users can share news (about themselves or the community), daily activities, and favorite contents and comment on different subjects freely. This has made the social network a rich source of information and has encouraged many researchers for discovering knowledge. Development of these medias has made the use of social media the most popular activity between web users.
Information in social media can be divided to 3 categories: textual information, linked information and time information. Since users have the most contribution in generating textual data, it plays an important role in discovering knowledge in textual content generation. Text messages in social media are short and have misspellings, idioms and abbreviation. Also, users are not ought to follow grammar rules. Thus, even with improvements in NLP techniques, because of the mentioned properties, processing textual messages in social medias is introduced as a challenge. Also, the structure of social media can be analyzed with the help of link information and the use of mathematic and graph theory (social network analysis).
Social networks are made of nodes and edges. Nodes represent people, organizations and groups that are members of the social network and edges represent connections (friendship, mutual interests, kinship and etc.) between the members.

Current members (A-Z)

Previous members (A-Z)



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