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Authors: Manabu Okumura 1 ; Yohei Yamaguchi 1 ; Masatomo Suzuki 2 and Hiroko Otsuka 2

Affiliations: 1 Tokyo Institute of Technology, Japan ; 2 Future University Hakodate, Japan

Keyword(s): Social Media, Twitter, Emotion Analysis, Readers’ Emotion.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Soft Computing ; Symbolic Systems ; Web Mining

Abstract: We present a rather new task of detecting and collecting tweets that contain heartwarming stories from a huge amount of tweets on Twitter in this paper. We also present a method for identifying heartwarming tweets. Our prediction method is based on a supervised learning algorithm in SVM along with features from the tweets. We found by comparing the feature sets that adding sentiment features mostly improves the performance. However, simply adding the features for detecting a story in a tweet (past tense and tweet length) cannot contribute to improving the performance, while adding all the features to the baseline feature set mostly yields the best performance from among the feature sets.

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Paper citation in several formats:
Okumura, M.; Yamaguchi, Y.; Suzuki, M. and Otsuka, H. (2014). Identifying Tweets that Contain a ’Heartwarming Story’. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR; ISBN 978-989-758-048-2; ISSN 2184-3228, SciTePress, pages 323-326. DOI: 10.5220/0005129503230326

@conference{kdir14,
author={Manabu Okumura. and Yohei Yamaguchi. and Masatomo Suzuki. and Hiroko Otsuka.},
title={Identifying Tweets that Contain a ’Heartwarming Story’},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR},
year={2014},
pages={323-326},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005129503230326},
isbn={978-989-758-048-2},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR
TI - Identifying Tweets that Contain a ’Heartwarming Story’
SN - 978-989-758-048-2
IS - 2184-3228
AU - Okumura, M.
AU - Yamaguchi, Y.
AU - Suzuki, M.
AU - Otsuka, H.
PY - 2014
SP - 323
EP - 326
DO - 10.5220/0005129503230326
PB - SciTePress

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