• Business Intelligence

      Mahroof, Kamran; Matthias, Olga; Hussain, Zahid I. (2017-06)
    • Identifying reputation collectors in community question answering (CQA) sites: Exploring the dark side of social media

      Roy, P.K.; Singh, J.P.; Baabdullah, A.M.; Kizgin, Hatice; Rana, Nripendra P. (2018-10)
      This research aims to identify users who are posting as well as encouraging others to post low-quality and duplicate contents on community question answering sites. The good guys called Caretakers and the bad guys called Reputation Collectors are characterised by their behaviour, answering pattern and reputation points. The proposed system is developed and analysed over publicly available Stack Exchange data dump. A graph based methodology is employed to derive the characteristic of Reputation Collectors and Caretakers. Results reveal that Reputation Collectors are primary sources of low-quality answers as well as answers to duplicate questions posted on the site. The Caretakers answer limited questions of challenging nature and fetches maximum reputation against those questions whereas Reputation Collectors answers have so many low-quality and duplicate questions to gain the reputation point. We have developed algorithms to identify the Caretakers and Reputation Collectors of the site. Our analysis finds that 1.05% of Reputation Collectors post 18.88% of low quality answers. This study extends previous research by identifying the Reputation Collectors and 2 how they collect their reputation points.
    • Large-scale data analysis using the Wigner function

      Earnshaw, Rae A.; Lei, Ci; Li, Jing; Mugassabi, Souad; Vourdas, Apostolos (2012)
      Large-scale data are analysed using the Wigner function. It is shown that the ‘frequency variable’ provides important information, which is lost with other techniques. The method is applied to ‘sentiment analysis’ in data from social networks and also to financial data.
    • The long game - technological innovation and the transformation of business performance

      Matthias, Olga; Fouweather, Ian (2021-04)
      This paper brings a new perspective to knowledge by focusing on the application and exploitation of big data in two UK companies providing, respectively, online and branch retailservices. The companies innovatively exploited the data that were generated by new internet technologies to improve business performance. The findings from both case study examples show that benefits do not come simply by adopting technology, but when people think creatively to exploit the potential benefits of ITC. The conclusion drawn is that the realisation of the ‘universal benefits’ of technological innovation does occur, but not necessarily until the hype has subsided. The paper demonstrates that there is opportunity to create sustainable competitive advantage through the application of ITC although the social, technological, and human challenges of managing technology have to be appreciated and managed. These implications need to be appreciated and if true long-term advantage isto be achieved.