Mining Social Media and DBpedia Data Using Gephi and R

Autor: Sadiq HUSSAIN, L. J. MUHAMMAD, Atomsa YAKUBU
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Journal of Applied Computer Science & Mathematics, Vol 12, Iss 1, Pp 14-20 (2018)
Druh dokumentu: article
ISSN: 2066-4273
2066-3129
DOI: 10.4316/JACSM.201801002
Popis: The big data is playing a big role in the field of machine learning and data mining. To extract meaningful and interesting information from big data mining is a challenge. The size of the data at social media and Wikipedia are increasing exponentially. To visualize such huge data is another aspect of big data. The roles of graphs are becoming important in case of visualization and modelling of such data. Gephi and R are two important visualization and exploration tools in this field. Using graph, one may find and calculate modularity, eccentricity, Indegree, Outdegree, betweenness centrality etc. In this paper, we had used Dbpedia, facebook and twitter datasets. We had used Gephi and R to look inside the structure of such data and comparing different statistics based on the graph by exploring the graphs.
Databáze: Directory of Open Access Journals