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Australasian Database Conference

ADC 2016: Databases Theory and Applications pp 467–470Cite as

Linking News and Tweets

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9877))

Abstract

In recent years, the rise of social media such as Twitter has been changing the way people acquire information. Meanwhile, traditional information sources such as news articles are still irreplaceable. These have led to a new branch of study on understanding the relationship between news articles and social media posts and fusing information from these heterogeneous sources. In this paper, we present a system that is able to effectively and efficiently link news and relevant tweets. Specifically, given a news stream and a tweet stream, the system discovers tweets that are relevant to each news in the news stream.

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Notes

  1. 1.

    https://twitter.com/.

  2. 2.

    https://www.facebook.com/.

  3. 3.

    The most popular microblogging platform in China. https://weibo.com.

  4. 4.

    http://www.cs.cmu.edu/~ark/TweetNLP/#tweeboparser_tweebank.

References

  1. Guo, W., Li, H., Ji, H., Diab, M.T.: Linking tweets to news: a framework to enrich short text data in social media. In: ACL, vol. 1, pp. 239–249. Citeseer (2013)

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  2. Kim, M., Newth, D., Christen, P.: Trends of news diffusion in social media based on crowd phenomena. In: Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion, pp. 753–758. International World Wide Web Conferences Steering Committee (2014)

    Google Scholar 

  3. Tsagkias, M., de Rijke, M., Weerkamp, W.: Linking online news and social media. In: Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, pp. 565–574. ACM (2011)

    Google Scholar 

  4. Yang, Z., Cai, K., Tang, J., Zhang, L., Su, Z., Li, J.: Social context summarization. In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 255–264. ACM (2011)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computing and Information Systems, The University of Melbourne, Melbourne, Australia

    Xiaojie Lin, Ye Gu & Rui Zhang

  2. Renmin University of China, Beijing, China

    Ju Fan

Authors
  1. Xiaojie Lin
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  2. Ye Gu
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  3. Rui Zhang
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  4. Ju Fan
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Corresponding author

Correspondence to Xiaojie Lin .

Editor information

Editors and Affiliations

  1. Monash University , Clayton, Australia

    Muhammad Aamir Cheema

  2. School of Comp. Science a. Engineer, University of New South Wales School of Comp. Science a. Engineer, Sydney, Australia

    Wenjie Zhang

  3. University of New South Wales , Sydney, New South Wales, Australia

    Lijun Chang

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© 2016 Springer International Publishing AG

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Cite this paper

Lin, X., Gu, Y., Zhang, R., Fan, J. (2016). Linking News and Tweets. In: Cheema, M., Zhang, W., Chang, L. (eds) Databases Theory and Applications. ADC 2016. Lecture Notes in Computer Science(), vol 9877. Springer, Cham. https://doi.org/10.1007/978-3-319-46922-5_41

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  • DOI: https://doi.org/10.1007/978-3-319-46922-5_41

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46921-8

  • Online ISBN: 978-3-319-46922-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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