User response to e-WOM in social networks: how to predict a content influence in Twitter
ZY Dahka, N Hajiheydari… - International Journal of …, 2020 - inderscienceonline.com
The purpose of this research is to find influential factors on electronic word-of-mouth
effectiveness for e-retailers in Twitter social media, applying data mining and text mining
techniques and through R programming language. The relationship between using hashtag,
mention, media and link in the tweet content, length of the content, the time of being posted
and the number of followers and followings with the influence of e-WOM is analysed. 48,129
tweets about two of the most famous American e-retailers, Amazon and eBay, are used as …
effectiveness for e-retailers in Twitter social media, applying data mining and text mining
techniques and through R programming language. The relationship between using hashtag,
mention, media and link in the tweet content, length of the content, the time of being posted
and the number of followers and followings with the influence of e-WOM is analysed. 48,129
tweets about two of the most famous American e-retailers, Amazon and eBay, are used as …
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