Abstract
Traditional citation networks which form the basis of study of community interaction tend to leave out a lot of articles which are related to a community but have not been directly cited by the members of it. As a result, the parameters estimated during the study of community interaction remain fairly inaccurate. In this work, we tend to perform a more accurate community interaction study by proposing a context-aware citation network which allows inclusion of papers to a community which have both direct as well as indirect relevance to the existing members of the community. A comparative analysis of computer science community networks built upon the proposed citation network and traditional citation network using the CiteSeer dataset show about 20–30% better results in favour of the former.
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Notes
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keywords here represent the set of keywords mentioned in papers + keywords extracted from the citation contexts of the paper.
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Saha, B., Anand, T., Sharma, A., Ghoshal, B. (2017). Improved Community Interaction Through Context Based Citation Analysis. In: Ghosh, A., Pal, R., Prasath, R. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2017. Lecture Notes in Computer Science(), vol 10682. Springer, Cham. https://doi.org/10.1007/978-3-319-71928-3_32
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DOI: https://doi.org/10.1007/978-3-319-71928-3_32
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