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|Homepage=https://wt-public.emm4u.eu/wassa2017/ | |Homepage=https://wt-public.emm4u.eu/wassa2017/ | ||
|City=Copenhagen | |City=Copenhagen | ||
| − | |Country= | + | |Country=Country:DK |
|has general chair=Alexandra Balahur, Saif M. Mohammad, Erik van der Goot | |has general chair=Alexandra Balahur, Saif M. Mohammad, Erik van der Goot | ||
|has Keynote speaker=Iryna Gurevych, Aditya Joshi, Viktor Pekar | |has Keynote speaker=Iryna Gurevych, Aditya Joshi, Viktor Pekar | ||
| Line 20: | Line 20: | ||
|Start Date=2017/09/08 | |Start Date=2017/09/08 | ||
|Academic Field=Natural Language Processing | |Academic Field=Natural Language Processing | ||
| + | |Event Status=as scheduled | ||
| + | |Event Mode=on site | ||
}} | }} | ||
'''WASSA 2017''' was organized in conjunction to the Conference on Empirical Methods in Natural | '''WASSA 2017''' was organized in conjunction to the Conference on Empirical Methods in Natural | ||
Revision as of 15:00, 6 September 2022
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WASSA 2017 was organized in conjunction to the Conference on Empirical Methods in Natural Language Processing EMNLP 2017 on September 8th, 2017, in Copenhagen, Denmark.
TOPICS
We encourage the submission of long and short research and demo papers including, but not restricted to the following topics related to subjectivity, sentiment and social media analysis:
- Lexical semantic resources, corpora and annotations for subjectivity, sentiment and social media analysis; (semi-)automatic corpora generation and annotation
- The use of semantic resources and methods (knowledge bases, semantic representations, inference mechanisms) for subjectivity, sentiment and emotion analysis;
- Opinion retrieval, extraction, categorization, aggregation and summarization
- Trend detection in social media using subjectivity and sentiment analysis techniques
- Data linking through social networks based on affect-related NLP methods
- Impact of affective data from social media
- Mass opinion estimation based on NLP and statistical models
- Online reputation management
- Topic and sentiment studies and applications of topic-sentiment analysis
- Domain, topic and genre dependency of sentiment analysis
- Ambiguity issues and word sense disambiguation of subjective language
- Pragmatic analysis of the opinion mining task
- Use of Semantic Web technologies for subjectivity and sentiment analysis
- Improvement of NLP tasks using subjectivity and/or sentiment analysis
- Intrinsic and extrinsic evaluations subjectivity and sentiment analysis
- Subjectivity, sentiment and emotion detection in social networks
- Classification of stance in dialogues
- Applications of sentiment and social media analysis systems
Apart from that, for the first time, we presented a shared task on automatically detecting intensity of emotion felt by the speaker of a tweet: WASSA-2017 Shared Task on Emotion Intensity. Twentytwo teams participated in the shared task, with results that showcase the latest developments in the theoretical and applied areas of Sentiment Analysis and Opinion Mining.
