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https://dspace.iiti.ac.in/handle/123456789/11430
Title: | Hashtag recommendation for enhancing the popularity of social media posts |
Authors: | Chakrabarti, Purnadip Malvi, Eish Bansal, Shubhi Kumar, Nagendra |
Keywords: | Social networking (online);Hashtag recommendation;Hashtags;Information spread;Non-uniform;Novel methods;Popularity predictions;Reachability;Social media;Social media analysis;Social media platforms;Data mining |
Issue Date: | 2023 |
Publisher: | Springer |
Citation: | Chakrabarti, P., Malvi, E., Bansal, S., & Kumar, N. (2023). Hashtag recommendation for enhancing the popularity of social media posts. Social Network Analysis and Mining, 13(1) doi:10.1007/s13278-023-01024-9 |
Abstract: | Social media has gained huge importance in our lives wherein there is an enormous demand of getting high social popularity. With the emergence of many social media platforms and an overload of information, attaining high popularity requires efficient usage of hashtags, which can increase the reachability of a post. However, with little awareness about using appropriate hashtags, it becomes the need of the hour to build an efficient system to recommend relevant hashtags which in turn can enhance the social popularity of a post. In this paper, we thus propose a novel method hashTag RecommendAtion for eNhancing Social popularITy to recommend context-relevant hashtags that enhance popularity. Our proposed method utilizes the trending nature of hashtags by using post keywords along with the popularity of users and posts. With the prevalent evaluation techniques of this field being quite unreliable and non-uniform, we have devised a novel evaluation algorithm that is more robust and reliable. The experimental results show that our proposed method significantly outperforms the current state-of-the-art methods. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature. |
URI: | https://doi.org/10.1007/s13278-023-01024-9 https://dspace.iiti.ac.in/handle/123456789/11430 |
ISSN: | 1869-5450 |
Type of Material: | Journal Article |
Appears in Collections: | Department of Electrical Engineering |
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