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"Research is what I'm doing when I don't know what I'm doing." ~ Wernher von Braun

Online Consumer Behaviour in Social Media Post Types: A Data Mining Approach

Abstract

Our  research  focuses  in  justifying  the  performance  of  different  types  of  social  media  posts extracted from real posts in fashion and cosmetics Facebook business pages after a live video was introduced as a new posting type. The data we used include posts of a different nature like video, photos, statuses, and links. User engagement metrics consist of comments, shares, and reactions.

The dataset is analysed through a study of the averages of the different engagement metrics for different timeframes. We applied machine learning and data mining classification techniques on benchmarked dataset using the WEKA platform to highlight a variety of reactions on  different status posts.  Finally,  we  present  the  classified  posts  performances  upon  several status posts  and users’ reactions. We hope that our research will reveal to decision makers, marketers  and  managers  valuable  information  incorporating  new  social  media  strategy  for leveraging their fashion businesses.

Gkikas Dimitrios, Theodoridis Theodoros, Theodoridis Prokopis, Kavoura Androniki(2020). Online Consumer Behaviour in Social Media Post Types: A Data Mining Approach. Proceedings of the European Marketing Academy, 49th, (63455).

Available from: https://www.researchgate.net/publication/344769529_Online_Consumer_Behaviour_in_Social_Media_Post_Types_A_Data_Mining_Approach.