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AAAI Spring Symposium 2016 : AAAI Spring Symp. on Observational Studies through Social Media and Other Human-Generated Content

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Link: http://research.microsoft.com/en-us/events/ossm/
 
When Mar 21, 2016 - Mar 23, 2016
Where Stanford University
Submission Deadline Oct 9, 2015
Notification Due Nov 6, 2015
Categories    social media   human generated content
 

Call For Papers

While using the Internet and mobile devices, people create data, whether intentionally or unintentionally, through their interaction with messaging services, websites and other applications and devices. This means that experiments with heretofore unprecedented populations can be performed in a variety of topics. Our workshop will focus on observational studies which arise from these interactions and data, with a focus on experiments that can indicate causal inferences.

Human generated content in general, and social media in particular, are a rich repository of data for observational studies across many areas: public health, with research on prevalence of disease and on the effects of media on the development of disease; medicine, showing the ability to detect mental disease in individuals using social media; education, to optimize teaching and exams; and sociology, to prove theories previously tested on very small populations. These studies were conducted from data including social media, search engine logs, location traces, and other forms of human generated content.

While many past studies showed a correlation between variables of interest, some studies were able to show causal relationships through natural experiments or by linking data sources. Our workshop focuses on all aspects of causal inference from human generated content, with studies that developed novel methods of identifying and using natural experiments or other methods for inferring causality.

Topics include:

Interpreting user-generated data, including text, structured data, and temporal data.
Causal analyses in social media, for example, using propensity score matching and causal graphs.
Identifying natural experiments and using them to understand causal inferences
Identifying population, reporting and other biases in social media
Applications and domain-specific explorations
Novel methods for preserving privacy
Ethical codes and implications
General Format:

The symposium will consist of 2-3 days of invited and submitted talks, poster presentations, and panel discussions.

Submission Requirements:

We invite submissions of extended abstracts up to 4 pages in PDF format. Submissions should be made via the workshop web site (Submission link will be provided here). Submissions should not be anonymized. The program committee will select talks and poster presentations based on topical relevance, technical contribution and general interest to the community.

Organizing Committee: Please contact us if you have any questions.

Elad Yom-Tov (Microsoft Research, eladyt@microsoft.com);
Munmun De Choudhury (Georgia Tech, munmund@gatech.edu);
Emre Kıcıman (Microsoft Research, emrek@microsoft.com)

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