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Subject:
From:
Yuheng Hu <[log in to unmask]>
Reply To:
Yuheng Hu <[log in to unmask]>
Date:
Wed, 27 May 2015 17:53:26 -0700
Content-Type:
text/plain
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text/plain (104 lines)
[Apologies for cross-posting.]

 =============================================================================
EASM 2015: 1st International Workshop on Event Analytics using Social Media Data
http://easmworkshop.github.io/

in conjunction with the
IEEE International Conference on Data Mining (ICDM 2015)

Date: Nov 14, 2015
Location: Atlantic City, New Jersey, USA
 =============================================================================


Overview
--------------------------------------
Social media channels enjoy many advantages over traditional media
channels, such as ubiquity, mobility, immediacy, and seamless
communication in reporting, covering and sharing real-world events,
e.g., the Boston bombings, the NBA finals, and the U.S Presidential
elections. Given these advantages, social media posts such as tweets
can typically reflect events as they happen, in real-time. Despite
these benefits, social media channels also tend to be noisy, chaotic,
and overwhelming. As a result, the vast amount of noisy social media
data poses tremendous challenges for conducting in-depth analysis,
which is critical to applications for event playback, journalistic
investigation, storytelling, etc. The purpose of this workshop is to
bring together researchers that are working in a variety of areas that
are all related to the larger problem of analyzing and understanding
events using social media responses, to discuss: 1) what are the
recently developed machine learning and data mining techniques that
can be leveraged to address challenges in analyzing events using
social media data, and 2) from challenges in analyzing events, what
are the practical research directions in the machine learning and data
mining community.

EASM 2015 solicits regular technical papers of up to 6 pages following
the IEEE author guidelines as well as short papers of up to 2 pages.
Regular papers will be presented in an oral session. Short papers will
be presented in a demo or poster session. Submissions must be original
and not submitted to or accepted by any other conference or journal.
All submissions will be peer-reviewed by at least three Program
Committee members. The review process will be double-blind. Therefore,
authors must conceal their identity (no author names, no affiliations,
no acknowledgment of sponsors, no direct references to previous work).


Topics of interest include, but are not limited to:
--------------------------------------
Novel approaches for event analysis on social media
Novel approaches for detecting events from social media
Novel applications of event analysis, e.g., Multimedia and cross-media
event analysis.
Domain-specific social media mining and analytics, such as: sports
events analysis, political event analysis, etc
User modeling and personalization for event recommendation
Opinion mining and sentiment analysis using social media data
Evaluation techniques targeted at social media
Industrial practices and implementations of event analysis systems



Submission Instructions
--------------------------------------
High quality original submissions are solicited for oral and poster
presentation at the workshop. Papers should not exceed a maximum of 8
pages, and must follow the IEEE ICDM format requirements of the main
conference. All submissions will be peer-reviewed, and all accepted
workshop papers will be published in the proceedings by the IEEE
Computer Society Press.

Important Dates

Paper Submission: July 20, 2015
Author Notification: September 1, 2015.
Workshop: November 14, 2015.

Submission Site:
https://wi-lab.com/cyberchair/2015/icdm15/scripts/submit.php?subarea=S01&undisplay_detail=1&wh=/cyberchair/2015/icdm15/scripts/ws_submit.php


Organizing Committee
--------------------------------------
Yuheng Hu, IBM Research ([log in to unmask])
Yu-Ru Lin, University of Pittsburgh ([log in to unmask])
Subbarao Kambhampati, Arizona State University ([log in to unmask])

--
Regards,
Yuheng Hu
Research Staff Member
IBM Research Almaden
http://yuhenghu.com

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