Horizon CDT Research Highlights

Research Highlights

Understanding online rumour dissemination in social media

As information technology develops, social media has revolutionised the way people communicate and share information [1]. With social media, information can be created, consumed and exchanged more easily than ever before, and can get disseminated to an unprecedented width within a very short period of time. However, apart from valid information, social media also facilitates the dissemination of rumours [2]. Although viral marketing and other information dissemination studies have sought to examine what makes certain messages disseminate more than others, there lacks research that bridges information dissemination in social media and rumour. This study focuses on understanding online rumour message features and their influences on rumour dissemination in social media. Combining rumour theories with persuasion theories and emotion theories, this study uses social media data to investigate the factors that influence the dissemination of online rumour messages.

References

  1. Bampo, M., Ewing, M.T., Mather, D.R., Stewart, D., and Wallace, M. (2008) "The effects of the social structure of digital networks on viral marketing performance". Information Systems Research, 19 (3): 273–290.
  2. Oh, O., Agrawal, M., and Rao, H.R. (2013) "Community intelligence and social media services: A rumor theoretic analysis of Tweets during social crises". MIS Quarterly, 37 (2): 407–426.

Publications

  1. Li, B., Ch’ng, E., Chong, A.Y., and Bao, H. (2016) "Predicting online e-marketplace sales performances: A big data approach". Computers & Industrial Engineering, 101: 565-571. (SCI, EI, ABS 2)
  2. Bao, H., Li, B., Shen, J., and Hou, F. (2016) "Repurchase intention in the Chinese e-marketplace: Roles of interactivity, trust and perceived effectiveness of e-commerce institutional mechanisms". Industrial Management & Data Systems (IMDS), 116 (8): 1759 – 1778. (SCI, ABS 2)
  3. Chong, A.Y., Li, B., Ngai, E.W.T., Ch’ng, E., and Lee, F. (2016) "Predicting online product sales via online reviews, sentiments, and promotion strategies: A big data architecture and neural network approach". International Journal of Operations and Production Management (IJOPM), 36 (4): 358-383. (SSCI, ABS 4)
  4. Hou, F., Chong, A.Y., and Li, B. (2016) "Factors determining a firm’s innovativeness: an empirical study of Chinese e-commerce industry". The 20th Pacific Asia Conference on Information Systems (PACIS 2016), Chiayi, Taiwan, 27 June- 1 July, 2016.

This work was carried out at the International Doctoral Innovation Centre (IDIC). The authors acknowledge the financial support from Ningbo Education Bureau, Ningbo Science and Technology Bureau, China's MOST, and the University of Nottingham. The work is also partially supported by EPSRC grant no EP/G037574/1.