poster

To follow or not to follow: a feature evaluation

Authors:

Yanan Zhu and

Nazli GoharianAuthors Info & Claims

WWW '13 Companion: Proceedings of the 22nd International Conference on World Wide Web

May 2013

Pages 59 - 60

https://doi.org/10.1145/2487788.2487811

Published: 13 May 2013 Publication History

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Abstract

The features available in Twitter provide meaningful information that can be harvested to provide a ranked list of followees to each user. We hypothesize that retweet and mention features can be further enriched by incorporating both temporal and additional/indirect links from within user's community. Our empirical results provide insights into the effectiveness of each feature, and evaluate our proposed similarity measures in ranking the followees. Utilizing temporal information and indirect links improves the effectiveness of retweet and mention features in terms of nDCG.

References

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Cha, M., Haddadi, H., Benevenuto, F., and Gummadi, K. Measuring User Influence in Twitter: The Million Follower Fallacy. 4th AAAI Conf. on Weblogs and Social Media, 2011.

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Duan, Y., Jiang, L., Qin, T., Zhou, M., and Shum, H. An empirical study on learning to rank of tweets. 23rd ACL Conf. on Computational Linguistics (COLING), 2010.

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Kwak,H.,Lee, C., Park, H., Moon,S. What is Twitter, a Social Network or a News Media? 19th World Wide Web Conf. (WWW), 2010.

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Welch,M., He, D., Schonfeld,U.,and Cho, Junghoo.Topical Semantics of Twitter Links. 4th ACM Conf. on Web search and Data Mining (WSDM), 2011.

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Cited By

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Parker JYates AGoharian NFrieder O(2015)Health-related hypothesis generation using social media dataSocial Network Analysis and Mining10.1007/s13278-014-0239-85:1Online publication date: 5-Mar-2015
https://doi.org/10.1007/s13278-014-0239-8
Parker JWei YYates AFrieder OGoharian NRokne JFaloutsos C(2013)A framework for detecting public health trends with TwitterProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1145/2492517.2492544(556-563)Online publication date: 25-Aug-2013
https://dl.acm.org/doi/10.1145/2492517.2492544

Index Terms

To follow or not to follow: a feature evaluation
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking
    2. Retrieval tasks and goals

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Information & Contributors

Information

Published In

WWW '13 Companion: Proceedings of the 22nd International Conference on World Wide Web

May 2013

1636 pages

ISBN:9781450320382

DOI:10.1145/2487788

General Chairs:
Daniel Schwabe
PUC-Rio - Brazil
,
Virgílio Almeida
UFMG - Brazil
,
Hartmut Glaser
CGI.br - Brazil
,
Program Chairs:
Ricardo Baeza-Yates
Yahoo! Labs - Spain & Chile
,
Sue Moon
KAIST - South Korea

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 May 2013

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WWW '13

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NICBR
CGIBR

WWW '13: 22nd International World Wide Web Conference

May 13 - 17, 2013

Rio de Janeiro, Brazil

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WWW '13 Companion Paper Acceptance Rate 831 of 1,250 submissions, 66%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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Parker JYates AGoharian NFrieder O(2015)Health-related hypothesis generation using social media dataSocial Network Analysis and Mining10.1007/s13278-014-0239-85:1Online publication date: 5-Mar-2015
https://doi.org/10.1007/s13278-014-0239-8
Parker JWei YYates AFrieder OGoharian NRokne JFaloutsos C(2013)A framework for detecting public health trends with TwitterProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1145/2492517.2492544(556-563)Online publication date: 25-Aug-2013
https://dl.acm.org/doi/10.1145/2492517.2492544

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Measuring and Detecting Virality on Social Media: The Case of Twitter’s Viral Tweets Topic

What is Twitter, a social network or a news media?