Open AccessUser response to e-WOM in social networks: how to predict a content influence in Twitter
Author(s) -
Zohreh Yousefi Dahka,
Nastaran Hajiheydari,
Saeed Rouhani
Publication year - 2019
Publication title -
international journal of internet marketing and advertising
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.165
H-Index - 19
eISSN - 1741-8100
pISSN - 1477-5212
DOI - 10.1504/ijima.2019.10024249
Subject(s) - social media , advertising , social media marketing , relevance (law) , viral marketing , word of mouth , content (measure theory) , content marketing , social network (sociolinguistics) , business , marketing , computer science , digital marketing , world wide web , political science , mathematics , mathematical analysis , law