|
***********************************************************************************
CALL FOR PAPERS
AI4BigData'19 - Artificial Intelligence for Big Social Data Analysis
http://www.ir.disco.unimib.it/ai4bigdata19/
Special Track @ FLAIRS-32
The 32nd International FLAIRS Conference - Sarasota, Florida, USA - May 19-22, 2019
***********************************************************************************
AI4BigData is the AAAI FLAIRS Special Track on the application of Artificial
Intelligence tools for Big Data Analysis. The track includes data-related tasks
such as analysis, capture, curation, search, sharing, storage, transfer,
visualization, and information credibility and privacy, with a special focus on
social data on the Web.
***********************************************************************************
TOPICS OF INTEREST
The broader context of the Special Track comprehends Artificial Intelligence,
Information Retrieval, Natural Language Processing, Computational Social Science,
Web Mining, Semantic Web.
Topics of interest include but are not limited to:
- Sentiment Analysis: polarity detection and emotion recognition
- Social Network Analysis: community identification and authority discovery
- Visual Analytics: social media tools for navigation and visualization
- Social content and recommender systems
- Organization and group behavior on social media
- Cultural influences on the use and adoption of social media
- Text categorization: topic recognition and demographic identification
- Multi-modal affective computing and sentiment analysis
- Multi-domain & cross-domain evaluation
- Sentiment topic detection & trend discovery
- Predicting real-world phenomena based on social media
- Social innovation and change through social media
- Ethnographic studies of social media
- Online information credibility assessment
- Information/misinformation diffusion
- Trust and reputation in virtual communities
- Retrieval of credible information
- Gold standard datasets generation with respect to the credibility of information
- Credibility of crowdsourced data
***********************************************************************************
SUBMISSION GUIDELINES
Papers should not exceed 6 pages (4 pages for a poster) and are due by November 19,
2018. Interested authors should format their papers according to AAAI formatting
guidelines, by using the latest AAAI Press Word template or LaTeX macro package,
available on the conference Website: http://flairs-32.info/
Papers must be submitted as PDF files through the EasyChair conference system.
Authors should indicate the "Artificial Intelligence for Big Social Data Analysis"
track for submissions.
Paper submission site: https://easychair.org/conferences/?conf=flairs32
All FLAIRS papers are reviewed using a double-blind process. Author names and
affiliations MUST NOT appear on submitted papers (do NOT use a fake name for your
EasyChair login; your EasyChair account information is hidden from reviewers).
The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers
will be required to sign a form transferring copyright of their contribution to AAAI.
FLAIRS requires that there be at least one full author registration per paper.
***********************************************************************************
IMPORTANT DATES
November 19, 2018 – Paper submission deadline
January 21, 2019 – Paper acceptance notification
February 4, 2019 – Poster abstract submission
February 11, 2019 – Poster abstract notification
February 18, 2019 – AUTHOR registration
February 25, 2019 – Camera-ready version due
April 08, 2019 – Early registration
May 13, 2019 – Regular registration
May 19-22, 2019 – Conference
***********************************************************************************
ORGANIZATION
Special Track Co-Chairs
- Eric Bell, Pacific Northwest National Laboratory (USA), eric.bell [at] pnnl.gov
- Viviana Patti, University of Turin (Italy), patti [at] di.unito.it
- Marco Viviani, University of Milano-Bicocca (Italy), marco.viviani [at] unimib.it
***********************************************************************************
|
