Constructing Keyword Propagation Map of Facebook Pages

Social network visualization has been extensively studied in research in diffusion of information. This paper focuses on extracting propagated Facebook posts from keywords created by users and visualizing important information diffusion path in social network graph. Furthermore, some interesting propagation patterns of user behavior in online social network were discovered. Our research contributions could be summarized as follow: 1) A novel method was proposed to determine the keyword occurrence in online social network, 2) This research constructed the map of keyword propagation and visualized the propagation patterns among different groups of people and 3) a case study of social phenomena was shown. In sum, our work eventually could be applied to improve the performance of tracking keyword spread in social media and would be beneficial for greater understanding about user behavior.

[1]  Artur Karczmarczyk,et al.  Influencing Information Spreading Processes in Complex Networks with Probability Spraying , 2018, 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[2]  Quan Li,et al.  Visual analysis of retweeting propagation network in a microblogging platform , 2013, VINCI '13.

[3]  Shou-De Lin,et al.  Modeling and Visualizing Information Propagation in a Micro-blogging Platform , 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

[4]  Kostas E. Psannis,et al.  Social networking data analysis tools & challenges , 2016, Future Gener. Comput. Syst..

[5]  P. Santhi Thilagam,et al.  Diffusion models and approaches for influence maximization in social networks , 2016, 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[6]  Cong Quan,et al.  Visualization and pattern discovery of social interactions and repost propagation in Sina Weibo , 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

[7]  Xiaoru Yuan,et al.  D-Map: Visual analysis of ego-centric information diffusion patterns in social media , 2016, 2016 IEEE Conference on Visual Analytics Science and Technology (VAST).

[8]  Makarand Hastak,et al.  Social network analysis: Characteristics of online social networks after a disaster , 2018, Int. J. Inf. Manag..

[9]  Karen Spärck Jones A statistical interpretation of term specificity and its application in retrieval , 2021, J. Documentation.

[10]  Ingyu Lee Analyzing characteristics of information propagation on social network graphs , 2013, 2013 Proceedings of IEEE Southeastcon.

[11]  Lance Chun Che Fung,et al.  Automatic content extraction and visualization of Thai websites for improved information representation , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).