Mood sensing from social media texts and its applications

Nguyen, Thin, Phung, Dinh, Adams, Brett and Venkatesh, Svetha 2013, Mood sensing from social media texts and its applications, Knowledge and information systems, vol. 39, no. 3, pp. 1-36, doi: 10.1007/s10115-013-0628-8.

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Title Mood sensing from social media texts and its applications
Author(s) Nguyen, ThinORCID iD for Nguyen, Thin
Phung, DinhORCID iD for Phung, Dinh
Adams, Brett
Venkatesh, SvethaORCID iD for Venkatesh, Svetha
Journal name Knowledge and information systems
Volume number 39
Issue number 3
Start page 1
End page 36
Total pages 36
Publisher Springer
Place of publication Berlin, Germany
Publication date 2013
ISSN 0219-1377
Keyword(s) Hyper-community
Mood classification
Mood pattern
Mood sensing
Summary We present a large-scale mood analysis in social media texts. We organise the paper in three parts: (1) addressing the problem of feature selection and classification of mood in blogosphere, (2) we extract global mood patterns at different level of aggregation from a large-scale data set of approximately 18 millions documents (3) and finally, we extract mood trajectory for an egocentric user and study how it can be used to detect subtle emotion signals in a user-centric manner, supporting discovery of hyper-groups of communities based on sentiment information. For mood classification, two feature sets proposed in psychology are used, showing that these features are efficient, do not require a training phase and yield classification results comparable to state of the art, supervised feature selection schemes, on mood patterns, empirical results for mood organisation in the blogosphere are provided, analogous to the structure of human emotion proposed independently in the psychology literature, and on community structure discovery, sentiment-based approach can yield useful insights into community formation.
Language eng
DOI 10.1007/s10115-013-0628-8
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 920410 Mental Health
HERDC Research category C1 Refereed article in a scholarly journal
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