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- W2765932912 abstract "Big Data Analysis (BDA) has attracted considerable interest and curiosity from scientists of various fields recently. As big size and complexity of big data, it is pivotal to uncover hidden patterns, bursts of activity, correlations and laws of it. Complex network analysis could be effective method for this purpose, because of its powerful data organization and visualization ability. Besides the general complex software (Gephi), some bibliometrics software (Citespace and SCI2) could also be used for this analysis, due to their powerful data process and visualization functions. This paper presents a comparison of Citespace, SCI2 and Gephi from the following three aspects: (1) Data preprocessing. Citespace is time-consuming and laborious on merging synonyms. SCI2 is efficient and suitable for massive data. Both of them could remove duplicate records. However, Gephi lacks these. (2) Network extraction. Citespace pays more attention on temporal analysis, but SCI2 and Gephi pay less attention on it. Besides, Citespace and SCI2 could provide pruning algorithms highlight the main structure of social network, but Gephi lacks this. (3) Visualization. In Citespace, co-occurrence network could present time, frequency and betweenness centrality simultaneously; cluster view could label the clusters with phrases. However, SCI2 and Gephi provide more various layout algorithms to present network. Besides, they have a better edit-ability than Citespace on generated network." @default.
- W2765932912 created "2017-11-10" @default.
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- W2765932912 date "2017-03-01" @default.
- W2765932912 modified "2023-10-02" @default.
- W2765932912 title "Comparison of complex network analysis software: Citespace, SCI<sup>2</sup> and Gephi" @default.
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- W2765932912 doi "https://doi.org/10.1109/icbda.2017.8078800" @default.
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