Online social networks and always-connected mobile devices have created an immense opportunity that empowers citizens and organizations to communicate and coordinate effectively in the wake of critical events. Specifically, there have been many isolated examples of using Twitter to provide timely and situational information about emergencies to relief organizations, and to conduct ad-hoc coordination. However, there are few attempts that try to understand the full ramifications of using social networks in a more concerted manner for effective organizational sensemaking in such contexts. This multi-disciplinary project, spanning computational and social sciences, seeks to fill this gap.
This project seeks to leverage Twitter posts (tweets) as the primary source of citizen inputs and couple relevant content and network information along with microworld simulations involving human role players to measure effectiveness of various organized sensemaking strategies. To arrive at meaningful summaries of citizen input, tweet content is analyzed using a semantic content analysis by combining natural language techniques that are suitably fused with existing knowledge bases (GeoNames, Wikipedia). Content analysis is further enhanced by innovatively combining it with the dynamic analysis of the twitter network to realize concise and trustworthy information nuggets of potential interest to organizations and citizens. The resulting summaries will be fed to a suitably designed microworld simulation involving human actors to derive realistic settings for modeling disaster situations and typical organizational structures.
This project is expected to have a significant impact in the specific context of disaster and emergency response. However, elements of this research are expected to have much wider utility, for example in the domains of e-commerce, and social reform. From a computational perspective, this project introduces the novel paradigm of people-content-network analysis whose application is not just limited to organized sensemaking. For social scientists, it provides a platform that can be used to assess relative efficacy of various organizational structures using microworld simulations and is expected to provide new insights into the types of social network structures (mix of symmetric and asymmetric) that might be better suitable to propagate information in emergent situations. From an educational standpoint, the majority of funds will be used to train the next generation of interdisciplinary researchers drawn from the computational and social sciences. Participation of underrepresented groups, especially women, will be encouraged, and is anticipated. Datasets and software developed as part of this project will be made available to the broader research community here.
Keywords: Social Networking, Emergency Response, Content Analysis, Network Analysis, Organizational Sensemaking, Collaborative Decision Making.
Collaborative team of Wright State University (WSU) and Ohio State University (OSU):
- WSU PI/PM: Prof. Amit Sheth
- WSU Co-PIs: Prof. Valerie Shalin, Prof. John Flach (Department of Psychology, Human Factors/Industrial Organization Graduate Program)
- OSU PI: Prof. Srinivasan Parthasarathy
- Students: Andrew Hampton, Lu Chen, Hemant Purohit (WSU); Dave Fuhry, Yiye Ruan (OSU), Shreyansh Bhatt (WSU)
- Funding: This collaborative research is funded by the National Science Foundation under award IIS-1111182 to Wright State University (PI: Amit Sheth) and award IIS-1111118 to Ohio State University (PI: Srinivasan Parthasarathy), 09/01/2011 - 08/31/2014.
Collaborations under the Local and Global Outreach:
Societal Outreach via Media Coverage:
- Wright State Research Seeks Sense From Social Media to Aid in Emergencies, Wright Sate Press, Nov. 14, 2011
- Alumnus, Professor Study Social Media Usefulness During Disasters, Ohio State Press, Nov. 16, 2011
- Twitris: Taking Crisis Mapping to the Next Level, TechPresident, Jun 24, 2013
- Wright State Researchers Use Social Media and Web Information to Track Response Efforts During Natural Disasters, Wright State Press, Sept. 22, 2013
- Initiatives of Twitris team (led by Hemant Purohit):
- Oklahoma Tornado: Analyzing 2 Million Disaster Tweets from Oklahoma Tornado, iRevolution, May 29, 2013
- North India Floods: Using crisis mapping to aid Uttarakhand, The Hindu, Jun 27, 2013
- Creating awareness for tech-assisted response: Are we missing out on tech-aided disaster management in Uttarakhand?, The Hindu, Jul 17, 2013
- Phailin cyclone crisis-map: Likewise North India floods crisis-mapping, our initiative in collaboration with Google Crisis Response team and the digital humanitarian volunteers globally from different organizations (SBTF, OpenCrisis, Info4Disasters, HumanityRoad, etc.) and universities cited by: Times Of India, DNA, Business Standard, EfyTimes, Kochi Reporter, Gadget Garrio, GeoSpatial World, Global Resilience Systems, Oct 2013
- Twitris: A 360 degree social media analytics platform to assist decision making by providing multi-faceted analyses of social data: Spatio-Temporal-Thematic, People-Content-Network, Sentiment-Emotion-Subjectivity etc.
Talks and tutorials:
- A. Sheth, C. Castillo, P. Meier, H. Purohit. Crisis Mapping, Citizen Sensing and Social Media Analytics: Leveraging Citizen Roles for Crisis Response. ICWSM-13 tutorial, July 2013. (details, slides)
- H. Purohit, A. Sheth. Guest lectures on Crisis Informatics and Coordination: Leveraging Citizen Roles via Social Media for Disaster Response, Course I400/I590: Informatics in Disasters and Emergency Response, Indiana University, Fall 2013
- Dynamics of coordination behavior during emergency situations
H. Purohit, A. Hampton, V. Shalin, A. Sheth, J. Flach, S. Bhatt. What Kind of #Communication is Twitter? Mining #Psycholinguistic Cues for Emergency Coordination. Computers in Human Behavior (CHB) journal, Vol. 29, Issue 6, Nov. 2013, P 2438–2447 (In print; accessible online).
H. Purohit. Crisis Response Coordination in Online Communities. Doctoral Consortium at NSF SOCS Symposium, 2013.
H. Purohit, A. Hampton, S. Bhatt, V. Shalin, A. Sheth, J. Flach. An Information Filtering and Management Model for Twitter Traffic to Assist Crisis Response Coordination. Technical Report, Kno.e.sis Center, 2013. (Under Review)
H. Purohit, A. Hampton, V. Shalin, A. Sheth, J. Flach. Framework to Analyze Coordination in Crisis Response. Collaboration and Crisis Informatics, Workshop in conjunction with CSCW-2012.
H. Purohit, A. Hampton, V. Shalin, A. Sheth, J. Flach. What kind of #communication is Twitter? A psycholinguistic perspective on communication in Twitter for the purpose of emergency coordination. NSF SoCS Symposium, 2012.
Purohit et al. Automatically matching resource needs and offers for coordination of emergency relief resources. Technical Report, Kno.e.sis Center, 2013. (Under Review; available upon request)
J.M. Flach, D. Steele-Johnson, V.L. Shalin and G.C. Hamilton. Coordination and control in emergency response. To appear in: Badiru & Racz (eds.) Handbook of Emergency Response: A Human Factors and Systems Engineering Approach. Taylor & Francis, Anticpated Aug. 2013. (In press)
- Understanding community engagement and sustainability on Twitter
H. Purohit, Y. Ruan, D. Fuhry, S. Parthasarthy, A. Sheth. On the Role of Social Identity and Cohesion in Characterizing Online Social Communities. Technical Report, 2012. (Under Review)
Y. Ruan, H. Purohit, D. Fuhry, S. Parthasarthy, A. Sheth. Prediction of Topic Volume on Twitter. 4th Int'l ACM Conference on Web Science (WebSci), 2012.
Y. Ruan. On the Interplay of Social Network Connection, User and Content. Doctoral Consortium at NSF SoCS Symposium, 2012.
- Generic approaches for influence analysis in evolving communities on social media
H. Purohit, J. Ajmera, S. Joshi, A. Verma, A. Sheth. Finding Influential authors in Brand-page Communities. In Proceedings of the 6th Int'l AAAI Conference on Weblogs and Social Media (ICWSM), 2012.
- Extracting diverse sentiment expression with target dependent polarity and emotion identification
L. Chen, W. Wang and A. Sheth. Are Twitter Users Equal in Predicting Elections? A Study of User Groups in Predicting 2012 U.S. Republican Presidential Primaries . Proceedings of the Fourth International Conference on Social Informatics (SocInfo'12). December 5-8, 2012, Lausanne, Switzerland.
L. Chen, W. Wang, M. Nagarajan, S. Wang and A. Sheth. Extracting Diverse Sentiment Expressions with Target-dependent Polarity from Twitter. In Proceedings of the 6th International AAAI Conference on Weblogs and Social Media (ICWSM), 2012.
L. Chen. Extracting Diverse Sentiment Expressions With Target-dependent Polarity from Twitter. Doctoral Symposium at NSF SoCS Symposium, 2012.
Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan and Amit P. Sheth. Harnessing Twitter ‘Big Data’ for Automatic Emotion Identification . In Proceedings of International Conference on Social Computing (SocialCom), 2012.
Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth. Discovering Fine-grained Sentiment in Suicide Notes. Biomedical Informatics Insights, vol. 5 (Suppl. 1) pp. 137-145, 2012
- Behavior analysis of online users
Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan and Amit P. Sheth. Cursing in English on Twitter . In ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW'14), 2014.
- Community dynamics in the social networks
D. Fuhry, Y. Ruan and S. Parthasarathy. Local/Global Term Analysis for Discovering Community Differences in Social Networks. 4th Int'l ACM Conference on Web Science (WebSci), 2012.
D. Fuhry. Summarization, Search, and Community Analysis in Social Networks. Doctoral Symposium at NSF SoCS Symposium, 2012.
- Multi-faceted social media analytics platform: Spatio-Temporal-Thematic, People-Content-Network and
H. Purohit and A. Sheth. Twitris v3: From Citizen Sensing to Analysis, Coordination and Action. In Proceedings of the 7th International AAAI Conference on Weblogs and Social Media (ICWSM), 2013, Demo track.
A. Sheth, A. Jadhav, P. Kapanipathi, C. Lu, H. Purohit, G. A. Smith, W. Wang. Twitris- a System for Collective Social Intelligence. Encyclopedia of Social Network Analysis and Mining (ESNAM), 2013.
A. Smith, A. Sheth, A. Jadhav, H. Purohit, L. Chen, M. Cooney, P. Kapanipathi, P. Anantharam, P. Koneru and W. Wang. Twitris+: Social Media Analytics Platform for Effective Coordination. NSF SoCS Symposium, 2012.
- Dynamics of content driven networks
S. Parthasarathy. A Scalable Framework for Content+Network Analytics. NSF SoCS Symposium, 2012.
- Graph sparsification for community detection
V. Satuluri, S. Parthasarathy, Y. Ruan. Local Graph Sparsification for Scalable Clustering. ACM SIGMOD Int’l Conference on Management of Data, 2011. (Related work done for foundation to build for SoCS work)
Y. Ruan, D. Fuhry, S. Parthasarathy. Efficient community detection in large networks using content and links. ACM WWW International Conference on World Wide Web, 2013.
- High Dimensional Data analytics
D. Fuhry, Y. Zhang, V. Satuluri, A. Nandi, and S. Parathasarathy. PLASMA-HD: Probing the LAttice Structure and MAkeup of High-dimensional Data. (demo) VLDB 2013.
X. Yang, A. Ghoting, Y. Ruan, S. Parthasarathy. A Framework for Summarizing and Analyzing Twitter Feeds. ACM SIGKDD Int’l Conference on Knowledge Discovery and Data Mining, 2012.
Check out the summary of our research progress and proposed sensemaking framework here
Foundation of SOCS:
Checkout summaries for related research and projects here
Contact: Hemant Purohit
A quick summary of our analysis frameworks and systems: (see in full page)