[open-linguistics] [SenticNet] CFP: UAI MABSDA Workshop on opinion mining

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Mon May 5 02:27:42 UTC 2014

Apologies for cross-posting,

Submissions are invited for the 2nd international workshop on Multidisciplinary
Approaches to Big Social Data Analysis (MABSDA), a UAI'14 workshop exploring the
new frontiers of big data computing for opinion mining through machine learning
techniques, knowledge-based systems, adaptive and transfer learning, in order to
more efficiently retrieve and extract social information from the Web. The
workshop is going to be held in Quebec City on 27th July. For more information,
please visit: http://sentic.net/mabsda

As the Web rapidly evolves, Web users are evolving with it. In the era of social
connectedness, people are becoming increasingly enthusiastic about interacting,
sharing, and collaborating through social networks, online communities, blogs,
Wikis, and other online collaborative media. In recent years, this collective
intelligence has spread to many different areas, with particular focus on fields
related to everyday life such as commerce, tourism, education, and health,
causing the size of the Social Web to expand exponentially. The distillation of
knowledge from such a large amount of unstructured information, however, is an
extremely difficult task, as the contents of today's Web are perfectly suitable
for human consumption, but remain hardly accessible to machines. The opportunity
to capture the opinions of the general public about social events, political
movements, company strategies, marketing campaigns, and product preferences has
raised growing interest both within the scientific community, leading to many
exciting open challenges, as well as in the business world, due to the
remarkable benefits to be had from marketing and financial market prediction.

MABSDA aims to provide an international forum for researchers in the field of
big data computing for opinion mining and sentiment analysis to share
information on their latest investigations in social information retrieval and
their applications both in academic research areas and industrial sectors. The
broader context of the workshop comprehends information retrieval, natural
language processing, web mining, semantic web, and artificial intelligence.
Topics of interest include but are not limited to:
• Machine learning for sentiment mining
• Concept-level sentiment analysis
• Biologically-inspired opinion mining
• Sentiment identification & classification
• Association rule learning for opinion mining
• Time evolving opinion & sentiment analysis
• Multi-modal sentiment analysis
• Multi-domain & cross-domain evaluation
• Knowledge base construction & integration with opinion analysis
• Transfer learning of opinion & sentiment with knowledge bases
• Sentiment topic detection & trend discovery
• Social ranking
• Social network analysis
• Opinion spam detection

Paper submission and reviewing will be handled electronically via EasyChair.
Submissions should be formatted in the UAI format and papers (including figures
and text) are limited to 9 pages in length. An additional 10th page is allowed
containing only references. Optional submissions of supplementary materials are
allowed. However, reviewers are under no obligation to look at the submitted
supplementary materials, and will base their review primarily on the main paper.
Papers that are currently under review or have already been accepted or
published in a refereed venue, including conferences and journals, may not be
submitted. Authors are strongly encouraged to make data and code publicly
available when possible. The review process is double blind. Please make sure
that the submission does not disclose the author's identities or affiliation.
Selected, expanded versions of papers presented at the workshop will be invited
to a forthcoming Special Issue of Cognitive Computation on opinion mining and
sentiment analysis.

• May 31st, 2014: Submission deadline
• June 20th, 2014: Notification of acceptance
• July 1st, 2014: Final manuscripts due
• July 27th, 2014: Workshop date

• Erik Cambria, Nanyang Technological University (Singapore)
• Yunqing Xia, Tsinghua University (China)
• Newton Howard, MIT Media Laboratory (USA)

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