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)

UN SDGs

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

SDG 16 Peace, Justice and Strong Institutions

Keywords

bursty event
Emotional reaction
sentiment burst
sentiment index

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.",

keywords = "bursty event, Emotional reaction, sentiment burst, sentiment index",

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

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note = "Pacific-Asia Conference on Knowledge Discovery and Data Mining 2011, PAKDD 2011 ; Conference date: 24-05-2011 Through 27-05-2011",

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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

TY - GEN

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

AU - Nguyen, Thin

AU - Phung, Dinh

AU - Adams, Brett

AU - Venkatesh, Svetha

N1 - Conference code: 15th

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.

KW - bursty event

KW - Emotional reaction

KW - sentiment burst

KW - sentiment index

UR - https://www.scopus.com/pages/publications/84857769522

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

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AN - SCOPUS:84857769522

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - New Frontiers in Applied Data Mining - PAKDD 2011 International Workshops, Revised Selected Papers

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ER -

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

UN SDGs

Keywords

Access to Document

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Cite this