Abstract
We propose a method for computing user similarity based on a network representing the semantic relationships between the words occurring in the same tweet and the related topics. We use such specially crafted network to define several user profiles to be compared with cosine similarity. We also describe an initial experimental activity to study the effectiveness on a limited dataset.
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Mizzaro, S., Pavan, M., Scagnetto, I. (2015). Content-Based Similarity of Twitter Users. In: Hanbury, A., Kazai, G., Rauber, A., Fuhr, N. (eds) Advances in Information Retrieval. ECIR 2015. Lecture Notes in Computer Science, vol 9022. Springer, Cham. https://doi.org/10.1007/978-3-319-16354-3_56
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DOI: https://doi.org/10.1007/978-3-319-16354-3_56
Publisher Name: Springer, Cham
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