O.: Usefulness of sentiment analysis

Abstract

Abstract. What can text sentiment analysis technology be used for, and does a more usage-informed view on sentiment analysis pose new requirements on technology development? 1 Human emotion, attitude, mood, affect, sentiment, opinion, and appeal Analysis of sentiment in text is a new and rapidly growing field of study and application. This paper outlines some application areas for sentiment analysis technology, and discusses what requirements a technology for sentiment analysis of text should be able to answer to. The human sensations of emotion, attitude, mood, affect, sentiment, opinion, and appeal all contribute to the basic categories of sentiment analysis of text, but they have been studied in their own right for a long time. Traditionally, this has been done in the behavioural sciences; [9] but today also by information technologists, especially with respect to interaction design . "Emotion" , "attitude" , "mood" "affect", "sentiment" , and "appeal" are everyday words. No consensus beyond the general vernacular usage of the most common terms can currently be assumed, but mostly the usage tends to hold that affect or affective state is the more general term, emotion a momentary, mostly conscious sensation, and mood an affective frame over a longer time span, not necessarily consciously acknowledged by its holder. These affective aspects of human behaviour and information processing are studied in various ways with variously differing perspectives, but the assumptions of most researchers is that people are in continuously changing affective states of some sort; and that activities people engage in have emotional impact and that their decision making, behaviour, and performance are informed by the affective state of the user. This appears to be true even for very mundane tasks such as workplace tasks or accessing information items, but most importantly for the purposes of this paper, in producing and understanding information items, and, it is assumed, even to the extent that mood, with respect to some topic or facet of life, will colour and influence the understanding, generation, or processing of information on another quite different topic. Sentiment analysis of text typically assumes that lexical items found in the text carry attitudinal loading. Previous work on the loading of individual features and the affective reaction of human subjects to linguistic items on the level of words and term