Active Hash Tags (past 2 hours)
Active Users (past 2 hours)
This location analysis is based only on tweets which have location metadata (~10% of total volume). Be sure to select both time and region of interest to see spatio-temporal-thematic social signals.
Delay between animations:

The tag cloud starts by summarizing latest tweets for the event and evolves as new tweets arrive. Only those tweets with location information are shown on the map.

Note: This map and tag cloud are updated to the second based on the Sexual Violence activity on Twitter.

Map and tag cloud will be reset in 0 seconds.

The following list shows top 100 influential Twitter users while talking about a topic, which can be multi-faceted - thematic,person,organization etc. The following network shows the connectivity among these influential Twitter users about a topic chosen on left menu. Colors denote the user level characteristics such as sentiment polarity for the topic, political affiliation, profession etc. Here, we specifically decided to show the characteristics and connectivity of top users, because they have potential to drive the community for desired actions. (Please check our Insights tab for such examples) Wondering about Science behind it? Check here.

(Click on a user in the list or node in the network to see user profile)

Emerging Community Leaders to engage with
User Interaction Network of emerging leaders




User Attribute
  • Journalism
  • Activism
  • Academics
  • Art
  • Blogging
  • Business
  • Tech
  • Medical
  • Sports
  • Others

What is Twitris+?

A Semantic Social Web application with real-time monitoring and multi-faceted analysis of social signals to provide insights and a framework for situational awareness, in-depth event analysis and coordination, emergency response aid, reputation management etc.

Why Twitris+?

Users are sharing voluminous social data (800M+ active Facebook users, 1B+ tweets/week) through social networking platforms accessible by Web and increasingly via mobile devices. This gives unprecedented opportunity to decision makers-- from corporate analysts to coordinators during emergencies, to answer questions or take actions related to a broad variety of activities and situations: who should they really engage with, how to prioritize posts for actions in the voluminous data stream, what are the needs and who are the resource providers in emergency event, how is corporate brand performing, and does the customer support adequately serve the needs while managing corporate reputation etc. We demonstrate these capabilities using Twitris+.

Key Features

  1. Decision making analytics platform for multi-faceted analyses of social data: spatio-temporal-thematic, people-content-network, sentiment-emotion-subjectivity etc.
  2. Answering questions of interests to corporate analysts and event coordinators
  3. Extraction of insights from social signals: Aggregation and filtering of social data, web resources (news, Wikipedia pages, multimedia), SMS data, followed by applying background knowledge to perform multi-faced analyses.
  4. Applications beyond state-of-the-art research in social-computing, such as in Health 2.0, cyber-physical systems etc.

Research Details


Alan Smith, Ashutosh Jadhav , Hemant Purohit, Lu Chen, Michael Cooney, Pavan Kapanipathi, Pramod Anatharam, Wenbo Wang (Past Members: Karthik Gomadam, Meena Nagarajan)


Prof. Amit Sheth

Publications & Presentations:

Identifying Seekers and Suppliers in Social Media Communities to Support Crisis Coordination
Hemant Purohit, Carlos Castillo, Fernando Diaz, Amit Sheth, and Patrick MeierHemant Purohit, Andrew Hampton, Shreyansh Bhatt, Valerie L. Shalin, Amit Sheth and John Flach, Journal of CSCW, Springer, 2014 (to appear).

With Whom to Coordinate, Why and How in Ad-hoc Social Media Communities during Crisis Response
Hemant Purohit, Andrew Hampton, Shreyansh Bhatt, Valerie L. Shalin, Amit Sheth and John Flach, ISCRAM, May 2014.

Emergency-Relief Coordination on Social Media: Automatically Matching Resource Requests and Offers.
Hemant Purohit, Carlos Castillo, Fernando Diaz, Amit Sheth, and Patrick Meier, First Monday journal, Vol. 19, Issue 1, Jan 2014.

Twitris v3: From Citizen Sensing to Analysis, Coordination and Action
Hemant Purohit, Amit Sheth, ICWSM-13 Demo track.

What Kind of #Communication is Twitter? Mining #Psycholinguistic Cues for Emergency Coordination
Hemant Purohit, Andrew J. Hampton, Valerie L. Shalin, Amit Sheth, John Flach, Shreyansh Bhatt, Computers in Human Behavior (CHB) journal.

Twitris- a System for Collective Social Intelligence
Amit Sheth, Ashutosh Jadhav, Pavan Kapanipathi, Chen Lu, Hemant Purohit, Gary Alan Smith, Wenbo Wang, Encyclopedia of Social Network Analysis and Mining (ESNAM).

Are Twitter Users Equal in Predicting Elections? A Study of User Groups in Predicting 2012 U.S. Republican Presidential Primaries
Lu Chen, Wenbo Wang and Amit P. Sheth, In Proceedings of the Fourth International Conference on Social Informatics (SocInfo'12), 2012.

Harnessing Twitter 'Big Data' for Automatic Emotion Identification
Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan and Amit P. Sheth, In Proceedings of International Conference on Social Computing (SocialCom), 2012.

Topical Anomaly Detection from Twitter Stream
Pramod Anantharam, Krishnaprasad Thirunarayan, and Amit Sheth, Research Note: In the Proceedings of ACM Web Science 2012, Evanston, Illinois, June 22-24, 2012.

Extracting Diverse Sentiment Expressions with Target-dependent Polarity from Twitter
Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang and Amit P. Sheth, In Proceedings of the 6th International AAAI Conference on Weblogs and Social Media (ICWSM), 2012.

Twitris+: Social Media Analytics Platform for Effective Coordination
A. Smith, A. Sheth, A. Jadhav, H. Purohit, L. Chen, M. Cooney, P. Kapanipathi, P. Anantharam, P. Koneru and W. Wang, NSF SoCS Symposium, 2012.

Discovering Fine-grained Sentiment in Suicide Notes
Wenbo Wang, Lu Chen, Ming Tan, Shaojun Wang, Amit P. Sheth, Biomedical Informatics Insights, vol. 5 (Suppl. 1) pp. 137-145, 2012.

Prediction of Topic Volume on Twitter
Yiye Ruan, Hemant Purohit, Dave Fuhry, Srini Parthasarthy, Amit Sheth, 4th Int'l ACM Conference of Web Science (WebSci), 2012.

Framework for the Analysis of Coordination in Crisis Response
Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit Sheth and John Flach, Workshop in conjunction with CSCW-2012.

Personalized Filtering of the Twitter Stream
Pavan Kapanipathi, Fabrizio Orlandi, Amit Sheth, Alexandre Passant, 2nd workshop on Semantic Personalized Information Management at ISWC 2011.

Citizen Sensing - Mining Social Signals & Perceptions: Microsoft Research Faculty Summit
Amit Sheth, Invited Talk at Microsoft Research Faculty Summit 2011, Redmond, WA, July 19, 2011.

Understanding User-Community Engagement by Multi-faceted Features: A Case Study on Twitter
H. Purohit, Y. Ruan, A. Joshi, S. Parthasarathy, A. Sheth, Workshop on Social Media Engagement, in conjunction with WWW 2011.

Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications
Meenakshi Nagarajan,Amit Sheth,Selvam Velmurugan, Proc of the WWW 2011, March 28 - April 1, 2011, Hyderabad, India, ACM.

Twarql: Tapping into the Wisdom of the Crowd
P. Mendes, P. Kapanipathi, and A. Passant, Triplification Challenge 2010 at 6th International Conference on Semantic Systems (I-SEMANTICS), Graz, Austria, 1-3 September 2010. (Winner of Triplification Challenge 2010).

Linked Open Social Signals
Mendes PN, Passant A, Kapanipathi P, Sheth AP, WI2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI-10), Toronto, Canada, Aug. 31 to Sep. 3, 2010.

Understanding User-Generated Content on Social Media
Meenakshi Nagarajan, Understanding User-Generated Content on Social Media, Ph.D. Dissertation, Wright State University, 2010.

Multimodal Social Intelligence in a Real-Time Dashboard System
Daniel Gruhl, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Amit Sheth, VLDB Journal on 'Data Management and Mining for Social Networks and Social Media', 6 (2) 2010.

Twitris 2.0 : Semantically Empowered System for Understanding Perceptions From Social Data
A. Jadhav, H. Purohit, P. Kapanipathi, P. Ananthram, A. Ranabahu, V. Nguyen, P. Mendes, A. G. Smith, M. Cooney, A. Sheth, ISWC 2010 Semantic Web Application Challenge.

A Qualitative Examination of Topical Tweet and Retweet Practices
Meenakshi Nagarajan, Hemant Purohit, Amit Sheth, 4th Int'l AAAI Conference on Weblogs and Social Media, ICWSM 2010, pp. 295-298.

Some Trust Issues in Social Networks and Sensor Networks
Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Henson, Amit Sheth, Proceedings of 2010 International Symposium on Collaborative Technologies and Systems (CTS 2010), Chicago, IL, May 17-21, 2010.

Understanding Events Through Analysis Of Social Media
Amit Sheth, Hemant Purohit, Ashutosh Jadhav, Pavan Kapanipathi and Lu Chen, Technical Report, Kno.e.sis Center, 2010.

Spatio-Temporal-Thematic Analysis of Citizen-Sensor Data - Challenges and Experiences
Meenakshi Nagarajan, Karthik Gomadam, Amit Sheth, Ajith Ranabahu, Raghava Mutharaju and Ashutosh Jadhav, Tenth International Conference on Web Information Systems Engineering, October 5-7, 2009, 539 - 553.

Citizen Sensing, Social Signals, and Enriching Human Experience
A. Sheth, IEEE Internet Computing, July/August 2009, pp. 80-85.

Analysis and Monetization of Social Data
Amit Sheth, Panel on 'Semantifying Social Networks,' Semantic Technology Conference, June 16, 2009, San Jose, CA.

Semantic Integration of Citizen Sensor Data and Multilevel Sensing: A Comprehensive Path Towards Event Monitoring and Situational Awareness
Amit Sheth, From E-Gov to Connected Governance: the Role of Cloud Computing, Web 2.0 and Web 3.0 Semantic Technologies, Fall Church, VA, February 17, 2009.

Demo Video

Articles and Resources

OneIndia News (Sept 20, 2014)

Twitris supported highly impactful #JKFloodRelief initiative by VOICE team at @InCrisisRelief, via Need-to-Rescue and Influencer Analysis tools. Digital volunteers use social media, come together during Jammu floods

Hindustan Times (Sept 9, 2014)

Twitris supported highly impactful #JKFloodRelief initiative by VOICE team at via Social Media monitoring and Influencer Analyses. Digital soldiers emerge heroes in Kashmir flood rescue

CrisisNET blog by Ushahidi (Jun 18, 2014)

Integration of our crisis response research into CrisisNET project for leveraging social media- Who Helps When Crisis Hits?

Tutorial at the SIAM conference SDM-14 (Apr 24, 2014)

Leveraging Social Media and Web of Data for Crisis Response Coordination

iRevolution (Nov 11, 2013)

Initiative of Twitris team to support MicroMappers app, for helping UNOCHA- Digital Humanitarians: From Haiti Earthquake to Typhoon Yolanda

DNA (Oct 12, 2013)

Initiative of Twitris team for digital volunteer-driven Crisis Map- Google's Person Finder and Google Crisis Response Map for Phailin to help with crisis information

The Hindu news media (Jun 27, 2013)

Initiative of Twitris team for digital volunteer-driven Crisis Map- Using crisis mapping to aid Uttarakhand , Are we missing out on tech-aided disaster management in Uttarakhand? (November 8, 2012)

Election 2012: The Semantic Recap

New Tech Post and Technology Voice (April 9, 2012)

twitris: Social Media Analysis with Semantic Web Technology

Dayton Business Journal (Mar 7, 2012)

Wright State wins patent for analyzing text messages

Wright State University News Room (November 14, 2011)

Wright State research seeks sense from social media to aid in emergencies

Twitris Logos and Images for Media Use