Call for Papers

Social Media Mining

for Public Health Monitoring and Surveillance

At Pacific Symposium on Biocomputing (PSB) 2016

January 4-8, 2016

The Big Island of Hawaii

 

Motivation

Social networks have seen an unprecedented growth in terms of users worldwide (e.g., as of 11th July 2014, Twitter has over 645 million users and grows by an estimated 135,000 users every day, generating 9,100 tweets per second). The social networks form a platform for people to share, discuss, and update their views and opinions, and many share their health-related information both in generic social media (such as Twitter, Facebook or Instagram) and in health-related social networks (forums focusing specifically on health issues, such as DailyStrength or MedHelp). Advances in automated data processing, machine learning and natural language processing present the possibility of utilizing this massive data source for public health monitoring and surveillance, if only researchers address the methodological challenges unique to this media.

The use of social media for health monitoring and surveillance has indeed many drawbacks and difficulties, particularly if done automatically. For example, traditional NLP methods that are used on longer texts have proven to be inadequate when applied to short texts, such as those found in Twitter. Something seemingly simple, such as searching and collecting relevant postings has also proven to be quite challenging, given the amount of data and semantic heterogeneity (how people refer to the topic of interest in colloquial terms) inherent to the media.

This session invites researchers who are interested in automatic methods for the collection, extraction, representation, analysis, and validation of social media data for public health surveillance and monitoring, including epidemiological and behavioral studies. It serves as a unique forum to discuss novel approaches to text and data mining methods that respond to the specific requirements of social media and that can prove invaluable for public health surveillance.

Topics of interest include, but are not limited to:

 

         Detection and extraction of adverse drug reaction mentions in social media

         Mapping of disease and symptoms mentions in social media to standardized vocabularies

         Deriving prescription drug use and off-label use trends from social media

         Social media in precision medicine

         Virus spread monitoring using social media

         Myths and truths about disease discussed in social media

         Drug abuse and alcoholism incidence monitoring in social media

         Prediction/detection of abusive behavior using social media postings

         Disease incidence studies using social media

         Sentinel event detection using social media

         Search, collection, and analysis techniques for public health informatics using social media

         Natural language processing methods for health-related consumer-generated (colloquial) text

         Classifying health-related messages in social media

         Sentiment analysis of social media messages for disease surveillance

Session Organizers

Chair:

Graciela Gonzalez (Arizona State University)

Email: ggonzalez@asu.edu

 

Co-Chairs:

Matthew Scotch (Arizona State University)

Email: matthew.scotch@asu.edu

 

Karen Smith (Regis University)

Email: ksmith003@regis.edu

 

John Brownstein (Harvard Medical School)

Email: john.brownstein@childrens.harvard.edu

 

Abeed Sarker (Arizona State University)

Email: msarker1@asu.edu

 

Michael Paul (Johns Hopkins University)

Email: mpaul@cs.jhu.edu

 

Azadeh Nikfarjam (Arizona State University)

Email: anikfarj@asu.edu

 

Submission Information

 

Please note that the submitted papers are reviewed and accepted on a competitive basis. At least three reviewers will be assigned to each submitted manuscript.

 

Important Dates

Paper submissions due: July 27, 2015 August 3, 2015

Notification of paper acceptance: September 14, 2015

Final paper deadline: October 5, 2015 at 11:59pm PT

Registration opens: August 1, 2015 at noon PT

Travel award applications

PSB has been able to offer travel support to many attendees in the past. However, please note that no one is guaranteed travel support.

Available: August 1, 2015 at noon PT

Deadline: October 5, 2015 at noon PT

Decisions will be announced in mid-October.

For details, please see http://psb.stanford.edu/keydates.html

Abstract Submissions

Poster presenters will be provided with an easel and a poster board 32"W x 40"H (80x100cm). One poster from each paid participant is accepted.

Available: August 1

Deadline: November 17, 2015 at noon PT

Decisions will be announced in mid-October.

 

Paper Format

 

Please see the PSB paper format template and instructions at http://psb.stanford.edu/psb-online/psb-submit.

 

The file formats we accept are: postscript (*.ps) and Adobe Acrobat (*.pdf)). Attached files should be named with the last name of the first author (e.g. altman.ps or altman.pdf). Hardcopy submissions or unprocessed TeX or LaTeX files will be rejected without review.

 

Each paper must be accompanied by a cover letter. The cover letter must state the following:

   The email address of the corresponding author.

   The specific PSB session that should review the paper or abstract.

   The submitted paper contains original, unpublished results, and is not currently under consideration elsewhere.

   All co-authors concur with the contents of the paper.

 

Submitted papers are limited to twelve (12) pages in our publication format. Please format your paper according to instructions found at http://psb.stanford.edu/psb-online/psb-submit/. If figures cannot be easily resized and placed precisely in the text, then it should be clear that with appropriate modifications, the total manuscript length would be within the page limit.

Social Media Mining Shared Task

This year we hold a social media mining shared task which consists of different sub-tasks related to classification and extraction of adverse drug reaction information from social media. More details about the task descriptions can be found here:

http://psb.stanford.edu/workshop/wkshp-smm/