@inproceedings{9908d423fd064dbdbcbf55e38fe2b4e8,
title = "Mining expertise and interests from social media",
abstract = "The rising popularity of social media in the enterprise presents new opportunities for one of the organization's most important needs-expertise location. Social media data can be very useful for expertise mining due to the variety of existing applications, the rich metadata, and the diversity of user associations with content. In this work, we provide an extensive study that explores the use of social media to infer expertise within a large global organization. We examine eight different social media applications by evaluating the data they produce through a large user survey, with 670 enterprise social media users. We distinguish between two semantics that relate a user to a topic: expertise in the topic and interest in it and compare these two semantics across the different social media applications. Copyright is held by the International World Wide Web Conference Committee (IW3C2).",
keywords = "Enterprise, Enterprise 2.0, Expert finding, Expert recommendation, Expert search, Expertise location, Interest mining, People search, Social business, Social computing, Social media, Social software, Web 2.0",
author = "Ido Guy and Uri Avraham and David Carmel and Sigalit Ur and Michal Jacovi and Inbal Ronen",
year = "2013",
month = jan,
day = "1",
doi = "10.1145/2488388.2488434",
language = "English",
isbn = "9781450320351",
series = "WWW 2013 - Proceedings of the 22nd International Conference on World Wide Web",
publisher = "Association for Computing Machinery",
pages = "515--525",
booktitle = "WWW 2013 - Proceedings of the 22nd International Conference on World Wide Web",
note = "22nd International Conference on World Wide Web, WWW 2013 ; Conference date: 13-05-2013 Through 17-05-2013",
}