Open AccessOnline social network relationships influenced on a retweeting
Author(s) -
Iman K. Abbood,
Saad Talib Hasson
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v20.i2.pp1037-1043
Subject(s) - social media , microblogging , focus (optics) , social network (sociolinguistics) , computer science , correlation , world wide web , correlation coefficient , positive correlation , internet privacy , mathematics , machine learning , medicine , physics , geometry , optics
Social network users spending a lot of time to post, search, interact and read the news on blogging platforms. In this era, social media is becoming a suitable place for discovering and exchanging new updates. However, Common social media helps the user to share his news online by a one-click. The ease-of-use leads to present novel breaking news to show up first on micro blogs. Twitter is one of the well-known micro blogging platforms with more than 250 million users, in which retweeting is a manageable way to share and sawing news. It is significant to foretell the retweeting and influence in a social relationship. The Correlation Coefficient formula has been used to determine the level of correlation between a user and his retweeters (followers, friends, and strangers) in social networks. Such correlation can be reached by utilizing the collected user information on Twitter with some features which have a main effect on retweet behavior. In this study, the focus is on particular friends, followers, and a retweet to be the promising source of relationships between users of social media. Experimental results based on twitter dataset showed that the Correlation Coefficient formula can be used as a predicting model, and it is a general framework to gain better fulfillment in calculating the correlation between the user, friends, and followers in social networks.. Their influence on the accuracy in predicting a retweet is also accomplished.