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Classifying T witter favorites: Like, bookmark, or Thanks?
Author(s) -
Gorrell Genevieve,
Bontcheva Kalina
Publication year - 2016
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23352
Subject(s) - popularity , computer science , personalization , world wide web , context (archaeology) , variety (cybernetics) , relevance (law) , matching (statistics) , focus (optics) , promotion (chess) , artificial intelligence , psychology , social psychology , paleontology , statistics , physics , mathematics , optics , political science , law , biology , politics
Since its foundation in 2006, Twitter has enjoyed a meteoric rise in popularity, currently boasting over 500 million users. Its short text nature means that the service is open to a variety of different usage patterns, which have evolved rapidly in terms of user base and utilization. Prior work has categorized T witter users, as well as studied the use of lists and re‐tweets and how these can be used to infer user profiles and interests. The focus of this article is on studying why and how T witter users mark tweets as “favorites”—a functionality with currently poorly understood usage, but strong relevance for personalization and information access applications. Firstly, manual analysis and classification are carried out on a randomly chosen set of favorited tweets, which reveal different approaches to using this functionality (i.e., bookmarks, thanks, like, conversational, and self‐promotion). Secondly, an automatic favorites classification approach is proposed, based on the categories established in the previous step. Our machine learning experiments demonstrate a high degree of success in matching human judgments in classifying favorites according to usage type. In conclusion, we discuss the purposes to which these data could be put, in the context of identifying users' patterns of interests.