Abstract
The aim of present research is to examine the influence of identified factors on efficacy of electronic word-of-mouth (e-WOM) for selected e-retailers on social media platform Twitter, applying data mining technique through python software programming. Taking the use of different programming and context as a research gap, the relationship among three important factors viz; network related, text related and time related factors and their influence on e-WOM has been examined on randomly tracked 2582 tweets about two of the reputed Indian e-retailers, Snapdeal and Flipkart. This study may be of immense help to e-retailers in identifying their reference customers (influential customers) on social media platform which in turn may be channelized for the purpose of viral marketing and other communication campaigns.
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