[Apologies for cross-postings]

CALL FOR PAPERS

Welcome to the 1st International Workshop on Social Media Analytics for
Smart Cities (SMASC 2017)

https://sites.google.com/site/smasc2017/home

In conjunction with the ACM International Conference on Information and
Knowledge Management (CIKM 2017), Singapore

*Important dates*


*Paper submission due: August 18  2017 (extended)Notification of
acceptance: August 31 2017Workshop date: November 6 2017*


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In an increasingly digital urban setting, Connected & Concerned Citizens
typically give voice to their opinions on various civic topics online over
the social media.  Efficient and scalable analysis of these citizen voices
on social media to derive actionable insights is an essential need for
developing smart cities.  The very nature of the data namely its
heterogeneity and dynamism, the lack of large annotated corpora, and the
need for multi-dimensional analysis across space, time and semantics, makes
urban social media analytics challenging. This workshop is dedicated to the
theme of social media analytics for smart cities, with the aim of focusing
the interest of CIKM research community on the challenges in mining social
media data for urban informatics. We are interested in fostering cross
collaboration between researchers on information retrieval, social media
analytics, linguistics, social scientists, and civic authorities, to
develop scalable and practical solutions to the real life problems of
cities as voiced by their citizens in social media. The aim of this
workshop is to encourage researchers to develop techniques for urban
analytics of social media data, with specific focus on applying these
techniques to practical urban informatics applications of smart cities.


This workshop is dedicated to the theme of urban social media analytics for
smart cities, with the aim of focusing the interest of CIKM research
community on the challenges in mining social media data for urban
informatics.

Topics of interest include but not limited to


1.Combining space, time and semantic analysis of urban informatics sources
on social media

2.Novel visualization of  urban social media data  across spatio-temporal
dimensions

3.Natural language processing and  text mining techniques for urban
informatics

4.Semantic Web techniques for multi-sourced urban informatics data

5.Knowledge and non-obvious relation extraction across multiple social
media data sources for urban analytics

6.Handling noisy social media data on urban civic issues

7.Social media apps for urban informatics

8.Graph analysis of social media data for urban informatics

9.Case studies of leveraging social media data in real life civic
management and urban planning

10.Applications of social media citizen generated data on civic issues for
smart cities

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Submission Guidelines:

Authors are invited to make original, unpublished submissions that are not
previously published, accepted to be published, or being considered for
publication in any other forum.

1.Regular Research Papers: These papers should report original research
results or significant case studies. They should be at most 8 pages.
2.Application Papers. These papers will present novel urban informatic
applications of social media data. They should be at most 6 pages.
3.Position Papers. The extended abstracts will present novel research
directions or identify challenging problems. They should be at most 4 pages
4. Case Studies. The extended abstracts will present case studies from
real-life experiences of developing/deploying urban informatic applications
using social media data and/or challenges/issues faced. They should be at
most 4 pages.

Manuscripts should be submitted electronically, as PDF  formatted using the
ACM camera-ready templates (
http://www.acm.org/publications/proceedings-template). Full papers cannot
exceed 10 pages in length and short papers cannot exceed 4 pages in length.
Papers should be submitted through the SMASC online submission system (
https://easychair.org/conferences/submission_new.cgi?a=15156761;track=186905
).

All reviews will be double-blind, and submissions must be properly
anonymized. Lack of anonymization may result in rejection without review.
Submissions will receive an “accept” or “reject” decision based on the
version that was submitted.


Thanks and Regards,

Xiangnan He
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