Emotional reactions to real-world events in social networks

Thin Nguyen; Dinh Phung; Brett Adams; Svetha Venkatesh

doi:10.1007/978-3-642-28320-8_5

Emotional reactions to real-world events in social networks

Thin Nguyen, Dinh Phung, Brett Adams, Svetha Venkatesh

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

2 Citations (Scopus)

Abstract

A convergence of emotions among people in social networks is potentially resulted by the occurrence of an unprecedented event in real world. E.g., a majority of bloggers would react angrily at the September 11 terrorist attacks. Based on this observation, we introduce a sentiment index, computed from the current mood tags in a collection of blog posts utilizing an affective lexicon, potentially revealing subtle events discussed in the blogosphere. We then develop a method for extracting events based on this index and its distribution. Our second contribution is establishment of a new bursty structure in text streams termed a sentiment burst. We employ a stochastic model to detect bursty periods of moods and the events associated. Our results on a dataset of more than 12 million mood-tagged blog posts over a 4-year period have shown that our sentiment-based bursty events are indeed meaningful, in several ways.

Original language	English
Title of host publication	New Frontiers in Applied Data Mining - PAKDD 2011 International Workshops, Revised Selected Papers
Pages	53-64
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-642-28320-8_5
Publication status	Published - 7 Mar 2012
Externally published	Yes
Event	Pacific-Asia Conference on Knowledge Discovery and Data Mining 2011 - Shenzhen, China Duration: 24 May 2011 → 27 May 2011 Conference number: 15th https://link.springer.com/book/10.1007/978-3-642-20841-6 (Proceedings)

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7104 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Pacific-Asia Conference on Knowledge Discovery and Data Mining 2011
Abbreviated title	PAKDD 2011
Country/Territory	China
City	Shenzhen
Period	24/05/11 → 27/05/11
Internet address	https://link.springer.com/book/10.1007/978-3-642-20841-6 (Proceedings)

Keywords

bursty event
Emotional reaction
sentiment burst
sentiment index

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-642-28320-8_5

Cite this

Nguyen, T., Phung, D., Adams, B., & Venkatesh, S. (2012). Emotional reactions to real-world events in social networks. In New Frontiers in Applied Data Mining - PAKDD 2011 International Workshops, Revised Selected Papers (pp. 53-64). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7104 LNAI). https://doi.org/10.1007/978-3-642-28320-8_5

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title = "Emotional reactions to real-world events in social networks",

abstract = "A convergence of emotions among people in social networks is potentially resulted by the occurrence of an unprecedented event in real world. E.g., a majority of bloggers would react angrily at the September 11 terrorist attacks. Based on this observation, we introduce a sentiment index, computed from the current mood tags in a collection of blog posts utilizing an affective lexicon, potentially revealing subtle events discussed in the blogosphere. We then develop a method for extracting events based on this index and its distribution. Our second contribution is establishment of a new bursty structure in text streams termed a sentiment burst. We employ a stochastic model to detect bursty periods of moods and the events associated. Our results on a dataset of more than 12 million mood-tagged blog posts over a 4-year period have shown that our sentiment-based bursty events are indeed meaningful, in several ways.",

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author = "Thin Nguyen and Dinh Phung and Brett Adams and Svetha Venkatesh",

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Nguyen, T, Phung, D, Adams, B & Venkatesh, S 2012, Emotional reactions to real-world events in social networks. in New Frontiers in Applied Data Mining - PAKDD 2011 International Workshops, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7104 LNAI, pp. 53-64, Pacific-Asia Conference on Knowledge Discovery and Data Mining 2011, Shenzhen, China, 24/05/11. https://doi.org/10.1007/978-3-642-28320-8_5

Emotional reactions to real-world events in social networks. / Nguyen, Thin; Phung, Dinh; Adams, Brett et al.
New Frontiers in Applied Data Mining - PAKDD 2011 International Workshops, Revised Selected Papers. 2012. p. 53-64 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7104 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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T1 - Emotional reactions to real-world events in social networks

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AU - Phung, Dinh

AU - Adams, Brett

AU - Venkatesh, Svetha

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PY - 2012/3/7

Y1 - 2012/3/7

N2 - A convergence of emotions among people in social networks is potentially resulted by the occurrence of an unprecedented event in real world. E.g., a majority of bloggers would react angrily at the September 11 terrorist attacks. Based on this observation, we introduce a sentiment index, computed from the current mood tags in a collection of blog posts utilizing an affective lexicon, potentially revealing subtle events discussed in the blogosphere. We then develop a method for extracting events based on this index and its distribution. Our second contribution is establishment of a new bursty structure in text streams termed a sentiment burst. We employ a stochastic model to detect bursty periods of moods and the events associated. Our results on a dataset of more than 12 million mood-tagged blog posts over a 4-year period have shown that our sentiment-based bursty events are indeed meaningful, in several ways.

AB - A convergence of emotions among people in social networks is potentially resulted by the occurrence of an unprecedented event in real world. E.g., a majority of bloggers would react angrily at the September 11 terrorist attacks. Based on this observation, we introduce a sentiment index, computed from the current mood tags in a collection of blog posts utilizing an affective lexicon, potentially revealing subtle events discussed in the blogosphere. We then develop a method for extracting events based on this index and its distribution. Our second contribution is establishment of a new bursty structure in text streams termed a sentiment burst. We employ a stochastic model to detect bursty periods of moods and the events associated. Our results on a dataset of more than 12 million mood-tagged blog posts over a 4-year period have shown that our sentiment-based bursty events are indeed meaningful, in several ways.

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Nguyen T, Phung D, Adams B, Venkatesh S. Emotional reactions to real-world events in social networks. In New Frontiers in Applied Data Mining - PAKDD 2011 International Workshops, Revised Selected Papers. 2012. p. 53-64. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-28320-8_5

Emotional reactions to real-world events in social networks

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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Cite this