Recent years have marked the beginning and expansion of the Social Web, in which people freely express and respond to opinion on a whole variety of topics. While the growing volume of subjective information available allows for better and more informed decisions of the users, the quantity of data to be analyzed imposed the development of specialized Natural Language Processing (NLP) systems that automatically detect subjectivity in text and subsequently extract, classify and summarize the opinions available on different topics. Although these research fields have been highly dynamic in the past years, dealing with subjectivity in text has proven to be a complex, interdisciplinary problem that remains far from being solved. Its challenges include the need to address the issue from different perspectives and at different levels, depending on the characteristics of the textual genre, the language(s) treated and the final application for which the analysis is done.
The aim of the 4th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA 2013) is to continue the line of the previous three editions, bringing together researchers in Computational Linguistics working on Subjectivity and Sentiment Analysis and researchers working on interdisciplinary aspects of affect computation from text. Additionally, this year, we would like to extend the focus to Social Media phenomena and the impact of affect-related phenomena in this context.
Download the pdf version of the CFP.
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
- 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
We also encourage participants to provide demos of their systems, thus giving them the opportunity to obtain feedback on their achievements and issues. At the same time, with the help of demos, we aim at enriching the discussion forum with application-specific topics for debate.