
Under the domain of text mining, Sentiment Analysis is a field that is in progress these days. Sentiment analysis is the calculative analysis of views, sentiments, opinions and positivity or negativity of a text. This paper identifies the factors that are responsible for the different sentiments of a person regarding a particular entity. In this work, the objective is to categorize the factors that influence the system of sentiment analysis due to varied sentiments of an individual. The methodology of Interpretative Structure Modeling has been employed for identifying the driving power and the dependent power of the various elements influencing sentiment analysis.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
