Measuring and analyzing charisma on twitter using combination weighting and TOPSIS method

In this research, charisma has been measured at different levels of online social networks including charisma at the level of messages, individuals, and communities. First, the charisma-associated features have been extracted and then weighted by hybrid proposed methods. Eventually, measuring and ranking charisma has been investigated through technique for order preference by similarity to ideal situation (TOPSIS) as one of the leading multi-criteria decision-making methods. Through the proposed approach, the charisma of different messages, individuals, as well as implicit and explicit communities can be measured, ranked, and compared. In this research, eight datasets were collected from Twitter with different and diverse features. The results indicated that the charismatic messages and individuals of each dataset have been chosen properly and logically. Further, a method has been presented to measure the rate of charisma in every community which can be employed for comparing communities and predicting behavior in online communities.