| Category: ||E-CFP |
| Subject: ||CFP: Special issue of Internet Research on "The Power of Prediction with Social Media" |
| From: || |
| Email: ||dani_(on)_uniovi.es |
| Date received: ||24 Oct 2011 |
| Deadline: ||01 Jun 2011 |
Special issue on "The Power of Prediction with Social Media"
Special issue call for papers from Internet Research, ISSN:
1066-2243 Editor in Chief: Jim Jansen
Social media today provide an impressive amount of data about
users and their societal interactions, thereby offering computer
scientists, social scientists, economists, and statisticians many
new opportunities for research exploration. Arguably one of the
most interesting lines of work is that of forecasting future
events and developments based on social media data, as we have
recently seen in the areas of politics, finance, entertainment,
market demands, health, etc.
But what can successfully be predicted and why? Since the first
algorithms and techniques emerged rather recently, little is
known about their overall potential, limitations and general
applicability to different domains.
Better understanding the predictive power and limitations of
social media is therefore of utmost importance, in order to --for
example-- avoid false expectations, misinformation or unintended
consequences. Today, current methods and techniques are far from
being well understood, and it is mostly unclear to what extent or
under what conditions the different methods for prediction can be
applied to social media. While there exists a respectable and
growing amount of literature in this area, current work is
fragmented, characterized by a lack of common evaluation
approaches. Yet, this research seems to have reached a sufficient
level of interest and relevance to justify a dedicated special
This special issue aims to shape a vision of important questions
to be addressed in this field and fill the gaps in current
research by soliciting presentations of early research on
algorithms, techniques, methods and empirical studies aimed at
the prediction of future or present events based on user
generated content in social media.
To address this guiding theme the special issue will be
articulated around, but not limited to, the following topics:
1. Politics, branding, and public opinion mining (e.g.,
electoral, market or stock market prediction).
2. Health, mood, and threats (e.g., epidemic outbreaks, social
3. Methodological aspects (e.g., data collection, data sampling,
privacy and data de-identification).
4. Success and failure case studies (e.g., reproducibility of
previous research or selection of baselines).
- Manuscript due date: June 1, 2012
- Decisions due: August 1, 2012
- Revised paper due: September 15, 2012
- Notification of acceptance: October 1, 2012
- Submission of final manuscript: October 31, 2012
- Publication date: late 2012 / early 2013 (tentative)
All submitted manuscripts should be original contributions and
not be under consideration in any other venue.
Publication of an enhanced version of a previously published
conference paper is possible if the review process determines
that the revision contains significant enhancements,
amplification or clarification of the original material. Any
prior appearance of a substantial amount of a submission should
be noted in the submission letter and on the title page.
Submissions must adhere to the "Author Guidelines" available at:
Detailed instructions will be announced later this year.
- Daniel Gayo-Avello, University of Oviedo (Spain),
- Panagiotis Takis Metaxas, Wellesley College and Harvard
University (USA), pmetaxas_(at)_seas.harvard.edu
- Eni Mustafaraj, Wellesley College (USA), emustafa_(at)_wellesley.edu
- Markus Strohmaier, Graz University of Technology (Austria),
- Harald Schoen, University of Bamberg (Germany),
- Peter Gloor, MIT (USA), pgloor_(at)_mit.edu
Feel free to contact the guest editors if you have any question.
- ELSNET mailing list Elsnet-list_(at)_elsnet.org
- To manage your subscription go to: