Mapping Twitter Topic Network for Information Sharing using NodeXL

Social media has a potential to be used as a professional and social networking to share interest. Users share similar interests on the Internet use social media such as Twitter. Despite the various existing methodologies on social media, there are many opportunities that need to be explored. The aim of this paper is to map the information shared on social media in order to identify relevant information. In order to achieve this aim, we examine user trends on sharing information on social media. We use NodeXL to obtain and analyse information from Twitter. The outcome of this paper contributes to a significant achievement that provides an important innovation in research methods in big data era to trace how information is shared across the social media and how to retrieve this information to assist decisionmaking process.

[1]  Murtaza Haider,et al.  Beyond the hype: Big data concepts, methods, and analytics , 2015, Int. J. Inf. Manag..

[2]  Laurie E. Damianos,et al.  Handshake: A Case Study for Exploring Business Networking for the Enterprise, Inside and Out , 2011, HCI.

[3]  P. Doreian.  Causality in Social Network Analysis , 2001 .

[4]  John Raacke,et al.  MySpace and Facebook: Applying the Uses and Gratifications Theory to Exploring Friend-Networking Sites , 2008, Cyberpsychology Behav. Soc. Netw..

[5]  Lon Safko,et al.  The Social Media Bible: Tactics, Tools, and Strategies for Business Success , 2009 .

[6]  Fei Liu,et al.  Recent developments in the organization goals conformance using ontology , 2013, Expert Syst. Appl..

[7]  Martin Hilbert,et al.  The World’s Technological Capacity to Store, Communicate, and Compute Information , 2011, Science.

[8]  A. Kaplan,et al.  Users of the world, unite! The challenges and opportunities of Social Media , 2010 .

[9]  Oren Etzioni,et al.  Named Entity Recognition in Tweets: An Experimental Study , 2011, EMNLP.

[10]  Guido Governatori,et al.  A modelling and reasoning framework for social networks policies , 2011, Enterp. Inf. Syst..

[11]  Yan Ma,et al.  Research of Hadoop-based data flow management system , 2011 .

[12]  Norjihan Abd Ghani,et al.  A sentiment-based filteration and data analysis framework for social media , 2015 .

[13]  Alexander Maedche,et al.  The Information Panopticon in the Big Data Era , 2014 .

[14]  Tao Huang,et al.  Promises and Challenges of Big Data Computing in Health Sciences , 2015, Big Data Res..

[15]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[16]  Emal Pasarly.  Time , 2011, Encyclopedia of Evolutionary Psychological Science.

[17]  Erik Qualman.  Socialnomics: How Social Media Transforms the Way We Live and Do Business , 2009 .

[18]  Sandra L. Calvert,et al.  College students' social networking experiences on Facebook , 2009 .

[19]  Laurie E. Damianos,et al.  Exploring the Adoption, Utility, and Social Influences of Social Bookmarking in a Corporate Environment , 2007, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[20]  Karen McIntyre,et al.  The Evolution of Social Media from 1969 to 2013: A Change in Competition and a Trend Toward Complementary, Niche Sites , 2014 .

[21]  Sue Abdinnour-Helm,et al.  Examining the effects of information system characteristics and perceived usefulness on post adoption usage of information systems , 2008, Inf. Manag..

[22]  Jyh-Shen Chiou,et al.  The impact of perceived ease of use on Internet service adoption: The moderating effects of temporal distance and perceived risk , 2010, Comput. Hum. Behav..

[23]  Kerk F. Kee,et al.  Being Immersed in Social Networking Environment: Facebook Groups, Uses and Gratifications, and Social Outcomes , 2009, Cyberpsychology Behav. Soc. Netw..

[24]  Camille Roth,et al.  Social and semantic coevolution in knowledge networks , 2010, Soc. Networks.

[25]  Estevam R. Hruschka,et al.  Tweet sentiment analysis with classifier ensembles , 2014, Decis. Support Syst..

[26]  Wu He,et al.  International Journal of Information Management Social Media Competitive Analysis and Text Mining: a Case Study in the Pizza Industry , 2022 .

[27]  Benjamin W. Wah,et al.  Significance and Challenges of Big Data Research , 2015, Big Data Res..

[28]  Mark Smith,et al.  Twitter as Mythmaker In Storytelling: The Emergence of Hero Status by the Boston Police Department in the aftermath of the 2013 Marathon Bombing , 2014 .

[29]  Kelty Logan,et al.  Social Media and News Gathering: Tapping into the Millennial Mindset , 2014 .

[30]  Stephanie M. Reich,et al.  Online and Offline Social Networks: Use of Social Networking Sites by Emerging Adults , 2008 .