LINGUIST List 28.934

Mon Feb 20 2017

Calls: Computational Linguistics/Denmark

Editor for this issue: Kenneth Steimel <>

Date: 17-Feb-2017
From: Saif Mohammad <>
Subject: 8th Workshop on Computational Approaches to Subjectivity
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Full Title: 8th Workshop on Computational Approaches to Subjectivity
Short Title: WASSA 2017

Date: 08-Sep-2017 - 08-Sep-2017
Location: Copenhagen, Denmark
Contact Person: Saif Mohammad
Meeting Email: < click here to access email >
Web Site:

Linguistic Field(s): Computational Linguistics

Call Deadline: 10-Jun-2017

Meeting Description:

The 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA 2017) will be held in conjunction with EMNLP-2017. Its aim is to continue the line of the previous 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, starting with WASSA 2013, we extended the focus to Social Media phenomena and the impact of affect-related phenomena in this context.

In 2017, we also include two shared tasks on emotions as part of the workshop. New labeled training and test data will be provided and participants can test their automatic systems on this common dataset. Papers describing the systems will be presented at the WASSA workshop, either as oral presentations (top scoring systems) or as posters.

Research in automatic Subjectivity and Sentiment Analysis (SSA), as subtasks of Affective Computing and Natural Language Processing (NLP), has flourished in the past years. The growth in interest in these tasks was motivated by the birth and rapid expansion of the Social Web that made it possible for people all over the world to share, comment or consult content on any given topic. In this context, opinions, sentiments and emotions expressed in Social Media texts have been shown to have a high influence on the social and economic behaviour worldwide. SSA systems are highly relevant to many real-world applications (e.g. marketing, eGovernance, business intelligence, social analysis, public health) and also many tasks in NLP – information extraction, question answering, textual entailment, to name just a few.

The importance of this field has been proven by the high number of approaches proposed in research in the past decade, as well as by the interest that it raised from other disciplines (Economics, Sociology, Psychology, Marketing, Crisis Management, Behavioral Studies) and the applications that were created using its technology.

In spite of the growing body of research in the area in the past years, dealing with affective phenomena 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, at different levels, and different modalities, depending on the characteristics of the textual genre, the language(s) treated and the final application for which the analysis is done. Additionally, SSA from Social Media texts has opened the way to many other types of analyses, linking textual data with images, social network metadata and social-media-specific text markings (e.g. Twitter hashtags).

Finally, the possibility to follow trends on opinions, while comparing and contrasting different sources of information (e.g. mainstream media vs. social media) allows for a more complete view and fairer opinion formation process.


- Alexandra Balahur:
- Saif M. Mohammad:
- Erik van der Goot:

Call for Papers:

In this new proposed edition, we would like to encourage the submission of long and short research and demo papers including, but not restricted to the following topics related to subjectivity and sentiment analysis:

- Resources 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
- Application of theories from other related fields (Neuropsychology, Cognitive Science, Psychology) to subjectivity and sentiment analysis
- Visualizing affect in traditional text sources as well as social media posts

Long Papers:

Long papers may consist of up to eight (8) pages of content, with two (2) additional pages of references, and will be presented orally.

Short Papers:

Short papers may consist of up to five (5) pages of content, and two (2) additional pages of references. The following types of papers are appropriate for a short paper submission:

- A paper describing the demonstration of a system
- A small, focused contribution
- Work in progress
- A negative result
- An opinion piece
- An interesting application nugget

Short papers will be presented either orally or as a poster. The choice of presentation will be given not based on the quality of the submission, but on the PC's recommendation relating to the most suitable presentation method.

A separate softconf link will be provided at a later date for submission of papers. Note that all submissions should be whole papers ready for review not abstracts.

Page Updated: 20-Feb-2017