Empirical Analysis of Factors Influencing Twitter Hashtag Recommendation on Detected Communities

Abstract

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Hashtag Recommendation Methods for Twitter and Sina Weibo: A Review

“…Although several studies [18,22,67] have highlighted the importance of user relations (behavioural and social), the degree of their influence is not clear. Alsini et al [16,19,23] present an overview of the community detection algorithms as techniques used to group like-minded users. The influence of four relations based on the hashtag usage, topics, followees and mentions on the performance of hashtag recommendation over communities have been investigated [23].…”

“…Social recommendation systems can be defined as techniques or algorithms that automatically suggest the most relevant and interesting data to social media users. Hashtag recommendation is a branch of the social recommendation systems that proposes contemporary and relevant hashtags to users as they type tweets [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Choosing the correct hashtag has several benefits: it enables the user to quickly join a discussion and read tweets written by other users [24].…”

“…Although researchers have investigated various techniques and factors that affect the performance of hashtag recommendation methods for Twitter/Sina Weibo data [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], there is a lack of a systematic review of these methods. Jain et al [30] listed only 11 methods in their survey on hashtag recommendations.…”