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Encyclopedia of Social Network Analysis and Mining pp 3212–3234Cite as

Twitris: A System for Collective Social Intelligence

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Synonyms

Citizen sensing; Community evolution; Event analysis on social media; Interaction network; People-content-network analysis; Real-time social media analysis; Semantic perception; Semantic Social Web; Sentiment-emotion-intent analysis; Social media analysis; Spatio-temporal-thematic analysis; Web 3.0

Glossary

Citizen Sensing:

Humans or citizens on the ubiquitous Web, acting as sensors and sharing their observations and views using mobile devices, mobile apps, and Web 2.0 services

Citizen-Sensor Network:

An interconnected network of people who actively observe, report, collect, coordinate, analyze, disseminate, and act upon information via text, links to other resources, and various media including audio, images, and videos

People-Content-Network Analysis (PCNA):

Social media analytics takes into account social media users (People), data shared on social media websites (Content), and the network of social media users (Network)

Semantic Web:

Semantic Web is a group of methods and...

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References

  • Battle C (2009) New media’s moment in Mumbai. Foreign Policy J, 15 Jan 2009. http://www.foreignpolicyjournal.com/2009/01/15/new-media. Accessed 25 Feb 2017

  • Brunn J (2016) Bots in the election. http://blog.knoesis.org/2016/12/bots-in-election.html. Accessed 9 Jan 2017

  • Chen L (2016) Subjectivity – tapping all the valuable insights beyond sentiment for nextgen information extraction. http://blog.knoesis.org/2016/09/subjectivity-tapping-all-valuable.html. Accessed 9 Jan 2017

  • Chen L, Wang W, Nagarajan M, Wang S, Sheth A (2012a) Extracting diverse sentiment expressions with target-dependent polarity from Twitter. In: Proceedings of the 6th international AAAI conference on weblogs and social media (ICWSM), Dublin, 5–7 June 2012

    Google Scholar 

  • Chen L, Wang W, Sheth AP (2012b) Are Twitter users equal in predicting elections? A study of user groups in predicting 2012 US Republican Presidential Primaries. In: International conference on social informatics. Springer, Berlin/Heidelberg, pp 379–392

    Chapter  Google Scholar 

  • Cognovi Labs (2016) Twitter analytics startup predicts trump upset in real-time. http://finance.yahoo.com/news/cognovi-labs-twitter-analytics-startup-181700129.html. Accessed 25 Feb 2017

  • Daniulaityte R, Carlson R, Brigham G, Cameron D, Sheth A (2015) “Sub is a weird drug:” a web-based study of lay attitudes about use of buprenorphine to self-treat opioid withdrawal symptoms. Am J Addict 24(5):403–409

    Article  Google Scholar 

  • Donovan J (2016) The Twitris sentiment analysis tool by Cognovi Labs predicted the Brexit hours earlier than polls. https://techcrunch.com/2016/06/29/the-twitris-sentiment-analysis-tool-by-cognovi-labs-predicted-the-brexit-hours-earlier-than-polls/. Accessed 25 Feb 2017

  • Gruhl D, Nagarajan M, Pieper J, Robson C, Sheth A (2010) Multimodal social intelligence in a real-time dashboard system. VLDB J (Data Manage Mining Soc Netw Soc Media) (Special issue, to appear) 19(6):825–848

    Google Scholar 

  • Hampton A, Bhatt S, Smith A, Brunn J, Purohit H, Shalin VL, Flach J, Sheth AP (2017) Constructing synthetic social media stimuli for an emergency preparedness functional exercise. In 14th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2017). Albi, Occitanie Pyrénées-Méditerranée, France

    Google Scholar 

  • Impact Lab (2008) Twitter provided a vital link in Mumbai terrorist attacks, 28 Nov 2008. http://www.impactlab.net/2008/11/28/twitter-provided-a-vital-link-in-mumbai-terrorist-attacks/. Accessed 25 Feb 2017

  • Jadhav A, Purohit H, Kapanipathi P, Ananthram P, Ranabahu A, Nguyen V, Mendes P, Smith AG, Cooney M, Sheth A (2010) Twitris 2.0: semantically empowered system for understanding perceptions from social data. In: Semantic web application challenge at ISWC, Shanghai, 7–11 Nov 2010

    Google Scholar 

  • Kapanipathi P, Orlandi F, Sheth A, Passant A (2011a) Personalized filtering of the Twitter stream. In: 2nd workshop on semantic personalized information management at ISWC 2011, Koblenz, 23–27 Oct 2011

    Google Scholar 

  • Kapanipathi P, Anaya J, Sheth A, Slatkin B, Passant A (2011b) Privacy-aware and scalable content dissemination in distributed social networks. In: International semantic web conference (ISWC), Koblenz, 23–27 Oct 2011

    Google Scholar 

  • Kapanipathi P, Jain P, Venkataramani C, Sheth A (2014) User interests identification on twitter using a hierarchical knowledge base. In: European semantic web conference, Springer, pp 99–113.

    Google Scholar 

  • Lamy FR, Daniulaityte R, Sheth A, Nahhas RW, Martins SS, Boyer EW, Carlson RG (2016) “Those edibles hit hard”: exploration of Twitter data on cannabis edibles in the US. Drug Alcohol Depend 164:64–70

    Article  Google Scholar 

  • Miller M, Banerjee D, Muppalla R, Romine D, Sheth D (2017) What are people tweeting about Zika? An exploratory study concerning symptoms, treatment, transmission, and prevention. arXiv preprint arXiv:1701.07490

    Article  Google Scholar 

  • Nagarajan M (2010) Understanding user-generated content on social media. PhD dissertation, Wright State University

    Google Scholar 

  • Nagarajan M, Gomadam K, Sheth A, Ranabahu A, Mutharaju R, Jadhav A (2009a) Spatio-temporal-thematic analysis of citizen-sensor data – challenges and experiences. In: Tenth international conference on web information systems engineering, Poznan, 5–7 Oct 2009

    Chapter  Google Scholar 

  • Nagarajan M, Baid K, Sheth A, Wang S (2009b) Monetizing user activity on social networks – challenges and experiences. In: IEEE/WIC/ACM international conference on web intelligence, Milan, 15–18 Sept 2009

    Google Scholar 

  • Nagarajan M, Purohit H, Sheth A (2010) A qualitative examination of topical tweet and retweet practices. In: 4th international AAAI conference on weblogs and social media (ICWSM), Washington, DC, 23–26 May 2010, pp 295–298

    Google Scholar 

  • Nagarajan M, Sheth A, Velmurugan S (2011) Citizen sensor data mining, social media analytics and development centric web applications. In: Proceedings of the WWW 2011, Hyderabad, 28 Mar, 1 Apr 2011

    Google Scholar 

  • Purohit H, Sheth AP (2013) Twitris v3: from citizen sensing to analysis, coordination and sction. In: ICWSM, pp 746–747

    Google Scholar 

  • Purohit H, Ruan Y, Joshi A, Parthasarathy S, Sheth A (2011) Understanding user-community engagement by multi-faceted features: a case study on Twitter. SoME 2011 (workshop on social media engagement, in conjunction with WWW 2011), Hyderabad, 28 Mar, 1 Apr 2011

    Google Scholar 

  • Purohit H, Ajmera J, Joshi S, Verma A, Sheth A (2012) Finding influential authors in brand-page communities. In: 6th international AAAI conference on weblogs and social media (ICWSM), Dublin, 5–7 June 2012

    Google Scholar 

  • Purohit H, Hampton A, Shalin VL, Sheth AP, Flach J, Bhatt S (2013a) What kind of# conversation is Twitter? Mining #psycholinguistic cues for emergency coordination. Comput Hum Behav 29(6):2438–2447

    Article  Google Scholar 

  • Purohit H, Castillo C, Diaz F, Sheth A, Meier P (2013b) Emergency-relief coordination on social media: automatically matching resource requests and offers. First Monday 19(1). http://firstmonday.org/ojs/index.php/fm/article/view/4848/3809

  • Purohit H, Meier P, Castillo C, Sheth AP (2013c) Crisis mapping, citizen sensing and social media analytics: leveraging citizen roles for crisis response. In: ICWSM tutorials. https://www.slideshare.net/knoesis/icwsm-2013-tutorial-crisis-mapping-citizen-sensing-and-social-media-analytics. Accessed 25 Feb 2017

  • Purohit H, Hampton A, Bhatt S, Shalin VL, Sheth AP, Flach JM (2014a) Identifying seekers and suppliers in social media communities to support crisis coordination. Computer Supported Cooperative Work (CSCW) 23(4-6):513–545

    Article  Google Scholar 

  • Purohit H, Bhatt S, Hampton A, Shalin VL, Sheth AP, Flach JM (2014b) With whom to coordinate, why and how in Ad-Hoc social media communications during crisis response. In: ISCRAM, pp 797–791

    Google Scholar 

  • Purohit H, Ruan Y, Fuhry D, Parthasarathy S, Sheth AP (2014c) On understanding the divergence of online social group discussion. ICWSM 14:396–405

    Google Scholar 

  • Purohit H, Dong G, Shalin V, Thirunarayan K, Sheth A (2015) Intent classification of short-text on social media. In: 2015 I.E. international conference on smart City/SocialCom/SustainCom (SmartCity), IEEE, pp 222–228

    Google Scholar 

  • Purohit H, Dalal M, Singh P, Nissima B, Moorthy V, Vemuri A, Krishnan V, Khursheed R, Balachandran S, Kushwah H, Rajgaria A (2016a) Empowering crisis response-led citizen communities: lessons learned from JKFloodRelief.org Initiative. In: Graham C (ed) Strategic management and leadership for systems development in virtual spaces. IGI Global, Hershey, pp 270–292. https://doi.org/10.4018/978-1-4666-9688-4.ch015

    Chapter  Google Scholar 

  • Purohit H, Banerjee T, Hampton A, Shalin V, Bhandutia N, Sheth A (2016b) Gender-based violence in 140 characters or fewer: a #BigData case study of Twitter. First Monday 21(1). https://doi.org/10.5210/fm.v21i1.6148

  • Ruan Y, Purohit H, Fuhry D, Parthasarthy S, Sheth A (2012) Prediction of topic volume on Twitter. In: 4th international ACM conference of web science (WebSci), Evanston, 22–24 June 2012

    Google Scholar 

  • Saxena V (2014) Digital soldiers emerge heroes in Kashmir flood rescue. Hindustan Times News. http://www.hindustantimes.com/floodfuryhitsjk/digital-soldiers-emerge-heroes-in-kashmir-flood-rescue/article1-1262099.aspx. Accessed 25 Feb 2017

  • Sheth A (2009a) Semantic integration of citizen sensor data and multilevel sensing: a comprehensive path towards event monitoring and situational awareness. In: From E-Gov to connected governance: the role of cloud computing, Web 2.0 and Web 3.0 semantic technologies, Fall Church, 17 Feb 2009

    Google Scholar 

  • Sheth A (2009b) Citizen sensing, social signals, and enriching human experience. IEEE Int Comput 13(4): 80–85

    Article  Google Scholar 

  • Sheth A (2011) Citizen sensing-opportunities and challenges in mining social signals and perceptions. In: Invited talk at microsoft research faculty summit 2011, Redmond, 19 July 2011

    Google Scholar 

  • Sheth A (2016a) #Brexit: “there is a big trouble for #remain” – some lessons from real-time #socialmedia analysis [LinkedIn article]. https://www.linkedin.com/pulse/brexit-big-trouble-remain-some-lessons-from-real-time-amit-sheth. Accessed 25 Feb 2017

  • Sheth A (2016b) Election day #SocialMedia analysis #Election2016 [LinkedIn article]. https://www.linkedin.com/pulse/election-day-socialmedia-analysis-election2016-06nov2016-amit-sheth?trk=prof-post. Accessed 25 Feb 2017

  • Sheth A, Thomas C, Mehra P (2010) Continuous semantics to analyze real-time data. IEEE Internet Comput 14(6):84–89

    Article  Google Scholar 

  • Thirunarayan K, Anantharam P (2011) Trust networks: interpersonal, sensor, and social. In: Proceedings of 2011 international conference on collaborative technologies and systems (CTS 2011), Philadelphia, 23–27 May 2011

    Google Scholar 

  • Wang W, Chen L, Thirunarayan K, Sheth A (2012) Harnessing Twitter ‘Big data’ for automatic emotion identification. In: Proceedings of international conference on social computing (SocialCom), 2012, Amsterdam, 3–5 Sept 2012

    Google Scholar 

  • Wang W, Chen L, Thirunarayan K, Sheth AP (2014) Cursing in english on twitter. In: Proceedings of the 17th ACM conference on computer supported cooperative work & social computing, ACM, pp 415–425

    Google Scholar 

  • Yazdavar AH, Al-Olimat HS, Banerjee T, Thirunarayan K, Pathak J, Sheth A (2016) Analyzing clinical depressive symptoms in Twitter. Paper presented at 23rd NIMH conference on mental health services research (MHSR): harnessing science to strengthen the public health impact, Bethesda

    Google Scholar 

  • Yuksel K, Biggemann S, Sheth A, Brunn J (2016) Using social media data to understand brand development. 2016 Direct/interactive marketing research summit (EDGE16), Los Angeles, 15 Oct 2016

    Google Scholar 

Recommended Reading

  • Sheth A, Thirunarayan K (2012) Semantics empowered Web 3.0: managing enterprise, social, sensor, and cloud-based data and services for advanced applications. Morgan & Claypool. ISBN: 1608457168

    Article  Google Scholar 

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Acknowledgments

We acknowledge contributions of these alumni and team members whose work has benefitted Twitris in different ways: Karthik Gomadam, Meena Nagarajan, and Ajith Ranabahu, and Pramod Anantharam, Shreyansh Bhatt, Prof. Krishnaprasad Thirunarayan, and Prof. Valerie Shalin. This work was partially supported by these NSF funded grants: “SoCS: Social Media Enhanced Organizational Sensemaking in Emergency Response” (IIS1111182), “I-Corps: Towards Commercialization of Twitris – a system for collective intelligence,” (1343041), and “PFI:AIR – TT: Market Driven Innovations and Scaling up of Twitris – A System for Collective Social Intelligence” (1542911). It is also partially supported by these NIH grants: “Modeling Social Behavior for Healthcare Utilization in Depression” (1 R01 MH105384-01A1) and “Trending: Social media analysis to monitor cannabis and synthetic cannabinoid use” (5R01DA039454-02). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the investigator(s) and do not necessarily reflect the views of the sponsor.

Author information

Authors and Affiliations

  1. Ohio Center of Excellence in Knowledge-Enabled Computing (Kno.e.sis), Wright State University, Dayton, OH, USA

    Amit Sheth, Hemant Purohit, Gary Alan Smith, Jeremy Brunn, Ashutosh Jadhav, Pavan Kapanipathi, Chen Lu & Wenbo Wang

  2. George Mason University, Fairfax, VA, USA

    Hemant Purohit

  3. IBM Research, Yorktown Heights, NY, USA

    Ashutosh Jadhav & Pavan Kapanipathi

  4. LinkedIn, Mountain View, CA, USA

    Chen Lu

  5. GoDaddy, Inc., San Francisco, CA, USA

    Wenbo Wang

Authors
  1. Amit Sheth
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  2. Hemant Purohit
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  3. Gary Alan Smith
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  4. Jeremy Brunn
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  5. Ashutosh Jadhav
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  6. Pavan Kapanipathi
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  7. Chen Lu
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  8. Wenbo Wang
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Corresponding author

Correspondence to Amit Sheth .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Reda Alhajj

  2. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Jon Rokne

Section Editor information

  1. Dept. of Computer Science, University at Albany, 1215 Western Ave, UAB 424B, Albany, NY, USA

    Charalampos Chelmis

  2. Department of Information Science, University of Arkansas at Little Rock, Little Rock, AR, USA

    Nitin Agarwal

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Sheth, A. et al. (2018). Twitris: A System for Collective Social Intelligence. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_345

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