Electronic Word-of-Mouth Spread in Twitter as a Function of Message Sentiment

Which is more viral, positive or negative electronic word-of-mouth? Can you tell which of the following tweets will spread more in Twitter: "saw the movie ... last night, must see it" or "saw the movie ... last night, avoid at any cost"? This study is about electronic Word-Of-Mouth spread as a factor of its sentiment. Some theories support a negative bias, while others support a positive bias. Some suggest that both biases are possible, depending on the product type. This paper presents the main theories, related studies and the results of quantitative research based on movie related tweets containing sentiment polarity. Due to the dual nature of Twitter, as mass medium and social network, the research focuses on Twitter's social sub network which contains ordinary users having a small to medium number of followers. The main findings are that tweets with positive sentiment polarity spread 15-20 percent more than tweets containing negative sentiment polarity. Keywords-Information flow; Information Dissemination; Sentiment Analysis; electronic Word Of Mouth; Twitter.