Details
| Original language | English |
|---|---|
| Title of host publication | WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web |
| Pages | 69-70 |
| Number of pages | 2 |
| Publication status | Published - 3 May 2013 |
| Event | 22nd International Conference on World Wide Web - Rio de Janeiro, Brazil Duration: 13 May 2013 → 17 May 2013 Conference number: 22 |
Publication series
| Name | WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web |
|---|
Abstract
Short films are regarded as an alternative form of artis- tic creation, and they express, in a few minutes, a whole gamma of different emotions oriented to impact the audience and communicate a story. In this paper, we exploit a multi-modal sentiment analysis approach to extract emo- tions in short films, based on the film criticism expressed through social comments from the video-sharing platform YouTube. We go beyond the traditional polarity detection (i.e., positive/negative), and extract, for each analyzed film, four opposing pairs of primary emotions: joy-sadness, anger- fear, trust-disgust, and anticipation-surprise.We found that YouTube comments are a valuable source of information for automatic emotion detection when compared to human anal- ysis elicited via crowdsourcing.
Keywords
- Sentiment analysis, Socialmedia analytics, Youtube
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
Cite this
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WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web. 2013. p. 69-70 (WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Mining Emotions in Short Films
T2 - 22nd International Conference on World Wide Web
AU - Orellana-Rodriguez, Claudia
AU - Diaz-Aviles, Ernesto
AU - Nejdl, Wolfgang
N1 - Conference code: 22
PY - 2013/5/3
Y1 - 2013/5/3
N2 - Short films are regarded as an alternative form of artis- tic creation, and they express, in a few minutes, a whole gamma of different emotions oriented to impact the audience and communicate a story. In this paper, we exploit a multi-modal sentiment analysis approach to extract emo- tions in short films, based on the film criticism expressed through social comments from the video-sharing platform YouTube. We go beyond the traditional polarity detection (i.e., positive/negative), and extract, for each analyzed film, four opposing pairs of primary emotions: joy-sadness, anger- fear, trust-disgust, and anticipation-surprise.We found that YouTube comments are a valuable source of information for automatic emotion detection when compared to human anal- ysis elicited via crowdsourcing.
AB - Short films are regarded as an alternative form of artis- tic creation, and they express, in a few minutes, a whole gamma of different emotions oriented to impact the audience and communicate a story. In this paper, we exploit a multi-modal sentiment analysis approach to extract emo- tions in short films, based on the film criticism expressed through social comments from the video-sharing platform YouTube. We go beyond the traditional polarity detection (i.e., positive/negative), and extract, for each analyzed film, four opposing pairs of primary emotions: joy-sadness, anger- fear, trust-disgust, and anticipation-surprise.We found that YouTube comments are a valuable source of information for automatic emotion detection when compared to human anal- ysis elicited via crowdsourcing.
KW - Sentiment analysis
KW - Socialmedia analytics
KW - Youtube
UR - http://www.scopus.com/inward/record.url?scp=84893094839&partnerID=8YFLogxK
U2 - 10.1145/2487788.2487816
DO - 10.1145/2487788.2487816
M3 - Conference contribution
AN - SCOPUS:84893094839
SN - 9781450320382
T3 - WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web
SP - 69
EP - 70
BT - WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web
Y2 - 13 May 2013 through 17 May 2013
ER -