Finding time-critical responses for information seeking in social media

Suhas Ranganath; Suhang Wang; Xia Hu; Jiliang Tang; Huan Liu

doi:10.1109/ICDM.2015.110

Finding time-critical responses for information seeking in social media

Suhas Ranganath, Suhang Wang, Xia Hu, Jiliang Tang, Huan Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

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.

Original language	English (US)
Title of host publication	Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015
Editors	Charu Aggarwal, Zhi-Hua Zhou, Alexander Tuzhilin, Hui Xiong, Xindong Wu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	961-966
Number of pages	6
ISBN (Electronic)	9781467395038
DOIs	https://doi.org/10.1109/ICDM.2015.110
State	Published - Jan 5 2016
Event	15th IEEE International Conference on Data Mining, ICDM 2015 - Atlantic City, United States Duration: Nov 14 2015 → Nov 17 2015

Publication series

Name	Proceedings - IEEE International Conference on Data Mining, ICDM
Volume	2016-January

Conference

Conference	15th IEEE International Conference on Data Mining, ICDM 2015
Country/Territory	United States
City	Atlantic City
Period	11/14/15 → 11/17/15

Keywords

Q&A
Situational Awareness
Timely Information

ASJC Scopus subject areas

General Engineering

Access to Document

10.1109/ICDM.2015.110

Cite this

Ranganath, S., Wang, S., Hu, X., Tang, J., & Liu, H. (2016). Finding time-critical responses for information seeking in social media. In C. Aggarwal, Z.-H. Zhou, A. Tuzhilin, H. Xiong, & X. Wu (Eds.), Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015 (pp. 961-966). Article 7373419 (Proceedings - IEEE International Conference on Data Mining, ICDM; Vol. 2016-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDM.2015.110

Finding time-critical responses for information seeking in social media. / Ranganath, Suhas; Wang, Suhang; Hu, Xia et al.
Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015. ed. / Charu Aggarwal; Zhi-Hua Zhou; Alexander Tuzhilin; Hui Xiong; Xindong Wu. Institute of Electrical and Electronics Engineers Inc., 2016. p. 961-966 7373419 (Proceedings - IEEE International Conference on Data Mining, ICDM; Vol. 2016-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ranganath, S, Wang, S, Hu, X, Tang, J & Liu, H 2016, Finding time-critical responses for information seeking in social media. in C Aggarwal, Z-H Zhou, A Tuzhilin, H Xiong & X Wu (eds), Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015., 7373419, Proceedings - IEEE International Conference on Data Mining, ICDM, vol. 2016-January, Institute of Electrical and Electronics Engineers Inc., pp. 961-966, 15th IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, United States, 11/14/15. https://doi.org/10.1109/ICDM.2015.110

Ranganath S, Wang S, Hu X, Tang J, Liu H. Finding time-critical responses for information seeking in social media. In Aggarwal C, Zhou ZH, Tuzhilin A, Xiong H, Wu X, editors, Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 961-966. 7373419. (Proceedings - IEEE International Conference on Data Mining, ICDM). doi: 10.1109/ICDM.2015.110

Ranganath, Suhas ; Wang, Suhang ; Hu, Xia et al. / Finding time-critical responses for information seeking in social media. Proceedings - 15th IEEE International Conference on Data Mining, ICDM 2015. editor / Charu Aggarwal ; Zhi-Hua Zhou ; Alexander Tuzhilin ; Hui Xiong ; Xindong Wu. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 961-966 (Proceedings - IEEE International Conference on Data Mining, ICDM).

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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.",

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AB - 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.

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Finding time-critical responses for information seeking in social media

Abstract

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Conference

Keywords

ASJC Scopus subject areas

Access to Document

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