Track Chairs

Anil Aggarwal, Professor, University of Baltimore, USA. Email: aaggarwal@ubalt.edu

Doug Vogel, Professor, Harbin Institute of Technology, China. Email: vogel.doug@gmail.com

G. 'Hari' Harindranath, Reader, Royal Holloway, University of London, UK. Email: G.Harindranath@rhul.ac.uk

Yuko Murayama, Professor, Tsuda University, Japan. Email: murayama@tsuda.ac.jp

Track Description

Information Systems for a Sharing Society

Digital Sharing has changed the world order. It is a major disruptive force which has transformed businesses, communication and everyday life of each and every individual. Digital sharing is diffusing worldwide from remote villages in Portugal to mountains of Siberia. It is engaging citizens in eparticipation resulting in reduction in government corruption by making them more accountable; enabling revolutions (Tahrir Square); tackling health education (Ebola virus spread) and much more. On the dark side it is also being misused for political purposes (Cambridge Analytica); Cyber attacks (alleged Russian meddling in Britexit and US elections) bullying and terrorism.  Fake news is making it complex to filter good from bad and creating doubts and authenticity of digital sharing.

Digital sharing, however, is a disruptive force to contend with. Citizens and users are building likeminded communities of people of all backgrounds they may never meet or even see. Given this disruptive revolution it is necessary to study ‘Why’ and ‘How’ it is happening and ‘When’ and ‘What’ we can expect from this revolution. 

Models are needed that can separate fake from real, good from bad and ugly. A 2 (fake/real) x 3 (good/bad/ugly) matrix need to be explored. It is a challenging task since digital media is borderless and uncontrolled. What kind of filters or semantic models would separate good from bad, fake from real? Can we rank order digital text based on its source, location, authenticity and value? Can we use history and/or density models to separate fake from real text/news. These and many other issues need to be studied. Some research has already started, for example, Pennycook et al (2018) discuss source quality; Safari et al (2018) discuss tweets credibility; Aggarwal (2016) discusses filtration of data; Li et al (2015) discuss credibility of sources; Lin et al (2016) discuss credibility indicators.

However, given the richness and research potential of this area, it is essential to brainstorm and bring diverse points of view to develop underlying theory and frameworks. This track will attempt to accomplish these objectives. Analytical techniques and emerging computing power is enabling researchers to address some of these questions.

There is no bigger digital sharing system than social media which reaches every corner of the world from a farmer in India to the queen of England. Information is shared every second between billions of people across the globe.  This track will address issues that would be most important as a global inclusive gateway which is ‘what’, ‘when’, why’ and ‘how’ of good, bad and the ugly in fake and real digital sharing environment.

We expect contributions from researchers within and beyond the information system discipline. The track invites both completed research papers and research in progress papers.

Possible Topics

The track will address issues related to participatory aspect of social networking in the context of various communities as well as the underlying theories of social inclusion, group dynamics, coordination, communications and behavioural and challenging aspects of social indulgence. 

Examples of topics include the following (but are not limited to):

• What is “fake’ news? Models to detect them?

• Impact of fake news: Standardization of fake news?

• Digital sharing -- a liar’s den?

• Models of digital sharing in borderless environment

• Influence of digital sharing – case studies (like Cambridge Analytica, election influences)

• What is ‘global’ and what is ‘local’ system in digital sharing?

• Use and misuse of digital sharing 

• Digital diffusion with respect to diversity

• Digital sharing systems: The new inclusive normal?

• Theories frameworks for investigating diversity and digital sharing

• Citizen sourcing and e-participation

• Empirical research related to diversity, inclusiveness and digital sharing

• Social network drivers of fake/real news

• Social-less world of social media

• Is social media sustainable?

• Crime and punishment of social media engagement

• The why, when, what and how of digital sharing

• political reward/punishment of anonymity

• Price of anonymity

• Impact of inclusion/exclusion in communities

• Trust and distrust in community engagement

• Security, privacy and risk associated with inclusiveness

• Case Studies (success/failures) related to behaviour standardisation 

• Digital sharing: an educational tool?

References:

Aggarwal, A (2016), A Hybrid Approach to Big Data Systems Development, in Managing Big data Integration in public Sector, published by IGI group., 20-37

Borsai, A. M. (2016). The Effects of Message Virality and Message Source on Facebook Users’ perceptions of Source Credibility, Norms, Attitudes, Emotional Responses, and Behavioral Intentions.

Lewandowsky, S., Cook, J., & Ecker, U. K. (2017). Letting the Gorilla Emerge From the Mist: Getting Past Post-Truth. Journal of Applied Research in Memory and Cognition, 6(4), 418-424.

Lazer, D. M., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., ... & Schudson, M. (2018).  The science of fake news. Science, 359(6380), 1094-1096.

Li, R., & Suh, A. (2015). Factors influencing information credibility on social media platforms: Evidence from Facebook Pages. Procedia computer science, 72, 314-328.

Lin, X., Spence, P. R., & Lachlan, K. A. (2016). Social media and credibility indicators: The effect of influence cues. Computers in Human Behavior, 63, 264-271.

Logsdon, J.; Patterson, K. (2009), “Deception in Business Networks: Is It Easier to Lie Online?”, Journal Of Business Ethics 90:537-549.

McCright, A. M., & Dunlap, R. E. (2017). Combatting misinformation requires recognizing its types and the factors that facilitate its spread and resonance. Journal of Applied Research in Memory and Cognition, 6(4), 389-396.

Marwick, A., & Lewis, R. (2017). Media manipulation and disinformation online. New York: Data & Society Research Institute.

Pavleska, T., Školkay, A., Zankova, B., Ribeiro, N., & Bechmann, A. (2018).  Performance analysis of fact-checking organizations and initiatives in Europe: a critical overview of online platforms fighting fake news.

 Pennycook, Gordon and Rand, David G., Crowdsourcing Judgments of News Source Quality (March 19, 2018). Available at SSRN: https://ssrn.com/abstract=3118471 or http://dx.doi.org/10.2139/ssrn.3118471 

Safari, Q., & Malek, M. R. (2018). A Spatial Approach for Credibility Assessment of Tweets in Case of Natural Disaster. In Adjunct Proceedings of the 14th International Conference on Location Based Services (pp. 179-183). ETH Zurich.

Shu, Kai, Suhang Wang, and Huan Liu. "Exploiting Tri-Relationship for Fake News Detection." arXiv preprint arXiv:1712.07709 (2017).

Stieglitz S, Dang-Xuan L. (2013), “Emotions and Information Diffusion in Social Media-Sentiment of Microblogs and Sharing Behavior”, Journal Of Management Information Systems. 29(4), pp. 217-248.

Stout, M. (2017). Covert Action in the Age of Social Media. Georgetown Journal of International Affairs, 18(2), 94-103.

Tenove, C., Buffie, J., McKay, S., Moscrop, D., Warren, M., & Cameron, M. DIGITAL THREATS TO DEMOCRATIC ELECTIONS. Available at https://democracy2017.sites.olt.ubc.ca/files/2018/01/DigitalThreats_Report-FINAL.pdf

Publishing Opportunities in Leading Journals

• Decision Support Systems 

• Information and Management

• Journal of MIS EJIS 

• ACM Transactions on Management Information Systems   

Track Associate Editors

1. Xusen Cheng, University of International Business and Economics, China

2. Sree Nilakanta, Iowa State University, USA

3. Edward W.N. Bernroider,Vienna University of Economics and Business, Austria

4. Nicholas Stangelo, Independent Consultant, USA

5. Devendra Bahadur Thapa, University of Agder, Norway

6. Sharma Pillutla, Towson university, USA

7. Irwin Brown, University of Capetown, South Africa

8. Dani Fowler, University of Baltimore, USA

9. Antonio Diaz Andrade, Auckland University of Technology, New Zealand

10. Giovanni Vincenti, University of Baltimore, USA

11. Priya Seetharaman, IIM Calcutta, India

12. Candace Deans, George Mason university, USA

13. Elsje Scott, University of Cape town, South Africa

14.  Stephen Jackson, Royal Holloway, University of London, UK 

15. Barbara Krumay, Johannes Kepler Universität Linz, Austria

16. Hajer Kefi, Paris School of Business, France

17. Rajesh Mirani, University of Baltimore, USA

18. Roberto Cavazos, University of Blatimore , USA