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JSAI International Symposium on Artificial Intelligence

JSAI-isAI 2015: New Frontiers in Artificial Intelligence pp 428–441Cite as

Aggregating and Analyzing Articles and Comments on a News Website

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10091))

Abstract

In the top news stories, the commenting activity is rising and falling until it stops. In some ongoing news stories such as disasters like the disappearance of flight MH370, global warming or climate change, political turmoil or economic crisis, this commenting activity cycle can repeat and last many years. To our knowledge, a study and analysis of those data does not exist up to now. There is a need to separate facts, opinions and junk within those comments data. In this paper, we present our framework for supporting readers in analyzing and visualizing facts, opinions and topics in the comments and its extension with comments aggregation and summarization for comments within several news articles for the same event. We added a time-series analysis and comments features such as surprising comments and a preferential threads attachment model.

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Notes

  1. 1.

    http://www.theguardian.com/world/malaysia-airlines-flight-mh370.

  2. 2.

    http://neo4j.com.

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Author information

Authors and Affiliations

  1. Faculty of Software and Information Science, Iwate Prefectural University, IPU, Takizawa, Sugo, 152-52, Japan

    David Ramamonjisoa

Authors
  1. David Ramamonjisoa
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Corresponding author

Correspondence to David Ramamonjisoa .

Editor information

Editors and Affiliations

  1. Chiba University Graduate School of Engineering, Chiba, Japan

    Mihoko Otake

  2. University of Tsukuba, Tokyo, Japan

    Setsuya Kurahashi

  3. Fujitsu Laboratories, Kanagawa, Japan

    Yuiko Ota

  4. National Institute of Informatics, Tokyo, Japan

    Ken Satoh

  5. Ochanomizu University, Tokyo, Japan

    Daisuke Bekki

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Ramamonjisoa, D. (2017). Aggregating and Analyzing Articles and Comments on a News Website. In: Otake, M., Kurahashi, S., Ota, Y., Satoh, K., Bekki, D. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2015. Lecture Notes in Computer Science(), vol 10091. Springer, Cham. https://doi.org/10.1007/978-3-319-50953-2_30

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  • DOI: https://doi.org/10.1007/978-3-319-50953-2_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50952-5

  • Online ISBN: 978-3-319-50953-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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