May 15, 2017

OSSM17: Observational Studies Through Social Media

Location: Montreal, Canada

Held at ICWSM 2017 (International AAAI Conference on Web and Social Media), Montreal, Canada, May 15, 2017

Workshop webpage: https://www.microsoft.com/en-us/research/event/ossm17/

CALL FOR CONTRIBUTIONS

The OSSM workshop will focus on observational studies (namely, causal analyses) of data traces created by people, whether directly or indirectly, through their interactions with social networks, messaging services, and other applications and devices.

Human generated content in general, including social media, has been shown to be 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 individual using social media; education, to optimize teaching and exams; and sociology, to prove theories previously tested on very small populations. These studies have been 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 and careful analyses. Natural experiments are empirical studies in which people are assigned to control or experimental conditions according to factors not under the control of investigators, where these factors resemble a random assignment. With Internet data, natural experiments occur frequently through policy changes, outside influences, and A/B testing. Our workshop will focus 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.

Studies based on human generated content require investigators to preserve the privacy of users and abide by proper ethical codes. We will encourage discussion of how these goals may be attained in secondary analysis of data such as that used in the aforementioned studies.

We are soliciting participation both from domain-experts interested in specific applications of methods, as well as methods-experts.

Topics of interest include, but are not limited to

  • Applications and domain-specific explorations
  • Interpreting user-generated data, including text, structured data, and temporal data
  • Causal analyses in social media, for example, through conditioning analyses, instrumental variables or regression discontinuity analysis
  • Identifying natural experiments and using them to understand causal inferences
  • Identifying and/or mitigating population, behavioral and other systematic biases in social media
  • Novel methods for preserving privacy in such experimentation
  • Ethical implications of such experiments
  • Qualitative, experimental and other evaluation and validation methods for observational study results

Submission should be extended abstracts of up to 4 pages and and will be published on the workshop webpage and optionally (depending on the author’s’ choice) in the ICWSM/AAAI workshop proceedings. We explicitly encourage the submission of preliminary work.

Authors whose papers are accepted to the workshop will be able to give a talk about their work (10min) and have the opportunity to participate in a poster session. In addition, the workshop will consist of structured discussion and breakout groups on topics pre-selected by participants. Potential outcomes of these discussions include a position paper, or potential research directions/ideas that could lead to interdisciplinary collaborations, particularly between computer and social scientists.

KEY DATES

  • Submission deadline: March 24, 2017
  • Author feedback: April 14, 2017
  • Workshop event (Montreal, Canada): May 15, 2017

Please see workshop webpage for formatting and submission instructions.

ORGANIZATION

Tim Althoff, Stanford University

Elad Yom-Tov, Microsoft Research

Munmun De Choudhury, Georgia Tech

Emre Kıcıman, Microsoft Research

CONTACT

Please direct your questions to ossm-workshop@googlegroups.com