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Towards the Elimination of the Miscommunication Between Users in Twitter

Tweet Classification Based on Expected Responses by User

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AI 2015: Advances in Artificial Intelligence (AI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9457))

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Abstract

In recent years, a Twitter response from another user who does not share the intentions and expectations of the original poster may cause discomfort and stress, which is a social phenomenon known as SNS fatigue. For example, a user may receive answers that are different from her/his expectation after the user posts a question on the timeline. In the background of such responses there is a miscommunication between users. In order to resolve the problem, it is important to know what the original poster expected as responses to her/his tweet. In this paper, we propose a classification method of tweets according to the response that users expect, and experimentally evaluate it. As a result, we have shown that tweets which the poster does not expect any replies can be classified with 76.2 % of the average precision.

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Notes

  1. 1.

    Twitter Streaming API: https://dev.twitter.com/streaming/overview.

  2. 2.

    JNI Kernel Extension for SVM-light: http://people.aifb.kit.edu/sbl/software/jnikernel/.

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Numbers 24300005, 26330081, 26870201.

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Correspondence to Tomoaki Ueda .

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Ueda, T., Orihara, R., Sei, Y., Tahara, Y., Ohsuga, A. (2015). Towards the Elimination of the Miscommunication Between Users in Twitter. In: Pfahringer, B., Renz, J. (eds) AI 2015: Advances in Artificial Intelligence. AI 2015. Lecture Notes in Computer Science(), vol 9457. Springer, Cham. https://doi.org/10.1007/978-3-319-26350-2_52

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  • DOI: https://doi.org/10.1007/978-3-319-26350-2_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26349-6

  • Online ISBN: 978-3-319-26350-2

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