TY - CHAP
T1 - Towards a general research framework for social media research using big data
AU - Lynn, Theodore
AU - Healy, Philip
AU - Kilroy, Steven
AU - Hunt, Graham
AU - Van Der Werff, Lisa
AU - Venkatagiri, Shankar
AU - Morrison, John
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/1
Y1 - 2015/9/1
N2 - The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a generalpurpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.
AB - The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a generalpurpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.
KW - big data analysis
KW - research framework
KW - Social media
KW - social media analytics
UR - https://www.scopus.com/pages/publications/84957928224
U2 - 10.1109/IPCC.2015.7235843
DO - 10.1109/IPCC.2015.7235843
M3 - Chapter
AN - SCOPUS:84957928224
T3 - IEEE International Professional Communication Conference
BT - ProComm 2015 - IEEE International Professional Communication Conference, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Professional Communication Conference, ProComm 2015
Y2 - 12 July 2015 through 15 July 2015
ER -