Appel: MABSDA

[Thierry Hamon]

Date: Mon, 31 Dec 2012 18:02:57 +0800
From: Erik Cambria <cambria at nus.edu.sg>
Message-ID: <40F05B37-E2D1-43E7-98E2-B5F0B7215350 at nus.edu.sg>
X-url: http://sentic.net/mabsda


Apologies for cross posting,

Submissions are invited for MABSDA (http://sentic.net/mabsda), the WWW13
workshop on sentiment analysis and big social data mining, to be held
this May in Rio de Janeiro, Brazil. The workshop aims to explore the new
frontiers of big data computing for opinion mining through Semantic Web
ontologies, rules, and services, Linked Data technologies, Web Science
applications, knowledge-based systems, adaptive and transfer learning,
in order to more efficiently retrieve and extract social information
from the Web.

ABSTRACT
As the Web rapidly evolves, Web users are evolving with it. In an era of
social connectedness, people are becoming more and more 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.


TOPICS
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
Semantic Web, Linked Open Data, Web Science, information retrieval, and
natural language processing. In addition to paper presentations, an
invited talk by Prof Bebo White will stress the interdisciplinary
challenges of big social data analysis. Topics of interest include but
are not limited to:

- Affective ontologies
- Rules for opinion mining
- Web Science approaches to sentiment analysis
- Linked Data applications for sentiment mining
- Sentiment identification & classification
- 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 and social network content analysis
- Sentic computing
- Opinion spam detection

INVITED SPEAKER
Bebo White is a Departmental Associate (Retired) at the Stanford Linear
Accelerator Center (SLAC), the high-energy physics and basic energy
science laboratory operated by Stanford University. Prior to his
retirement, he was permanent staff/faculty at SLAC from 1981 to
2005. While his initial responsibilities at SLAC were in computational
physics, in recent years Prof White's work has been dominated by his
involvement with World Wide Web technology. He first became involved
with WWW development while on sabbatical at CERN in 1989 and was
instrumental in establishing the first non-European Web site at SLAC in
1991.

TIMEFRAME
- February 25th, 2013: Due date for workshop papers
- March 13th, 2013: Notification of paper acceptance to authors
- April 3rd, 2013: Camera-ready of accepted papers
- May 13th, 2013: Workshop date

ORGANIZERS
- Erik Cambria, National University of Singapore (Singapore)
- Yunqing Xia, Tsinghua University (China)
- Newton Howard, MIT Media Laboratory (USA)

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