@inproceedings{694e765c0f464d699b7b918094b7cabe,
title = "Finding time-critical responses for information seeking in social media",
abstract = "Social media is being increasingly used to request information and help in situations like natural disasters, where time is a critical commodity. However, generic social media platforms are not explicitly designed for timely information seeking, making it difficult for users to obtain prompt responses. Algorithms to ensure prompt responders for questions in social media have to understand the factors affecting their response time. In this paper, we draw from sociological studies on information seeking and organizational behavior to model the future availability and past response behavior of the candidate responders. We integrate these criteria with their interests to identify users who can provide timely and relevant responses to questions posted in social media. We propose a learning algorithm to derive optimal rankings of responders for a given question. We present questions posted on Twitter as a form of information seeking activity in social media. Our experiments demonstrate that the proposed framework is useful in identifying timely and relevant responders for questions in social media.",
author = "Suhas Ranganath and Suhang Wang and Xia Hu and Jiliang Tang and Huan Liu",
year = "2016",
month = jan,
day = "5",
doi = "10.1109/ICDM.2015.110",
language = "English (US)",
series = "Proceedings - IEEE International Conference on Data Mining, ICDM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "961--966",
editor = "Charu Aggarwal and Zhi-Hua Zhou and Alexander Tuzhilin and Hui Xiong and Xindong Wu",
booktitle = "Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015",
address = "United States",
note = "15th IEEE International Conference on Data Mining, ICDM 2015 ; Conference date: 14-11-2015 Through 17-11-2015",
}