Exploiting emoticons in sentiment analysis

Abstract

As people increasingly use emoticons in text in order to express, stress, or disambiguate their sentiment, it is crucial for automated sentiment analysis tools to correctly account for such graphical cues for sentiment. We analyze how emoticons typically convey sentiment and demonstrate how we can exploit this by using a novel, manually created emoticon sentiment lexicon in order to improve a state-of-the-art lexicon-based sentiment classification method. We evaluate our approach on 2,080 Dutch tweets and forum messages, which all contain emoticons and have been manually annotated for sentiment. On this corpus, paragraph-level accounting for sentiment implied by emoticons significantly improves sentiment classification accuracy. This indicates that whenever emoticons are used, their associated sentiment dominates the sentiment conveyed by textual cues and forms a good proxy for intended sentiment.

A hybrid approach to the sentiment analysis problem at the sentence level

“…This research provided us with important lessons on the difficulties and potential pitfalls of embracing such a task and how to better deal with it. The other research effort is by Hogenboom et al [27,28] on the the use of emoticons as modifiers of the sentiment expressed in text and as vehicles of sentiment by themselves. According to the findings of the authors, the sentiment associated to emoticons dominates the sentiment conveyed by the text fragment in which these emoticons are embedded.…”

Sentiment Expression via Emoticons on Social Media- Twitter

“…There are ample studies carried on "sentiment analysis" in recent past years [1][2][3][4][5][6][7][8][9][10][11]. In particular, the applications of Sentiment Analysis has attracted many interests on social platforms, both in industry and academia.…”

Sentiment Analysis With Multilayer Perceptron Using Emoticon Space Model

“…Author Hogenboom et al [1] proposed a novel framework for automated sentiment analysis, which takes into account the information conveyed by emoticons. The goal of framework is to identify emoticons, decide their sentiment, and allocate the associated sentiment to the affected text in order to correctly classify the polarity of natural language text as either positive or negative.…”

“…Different strategies have developed to use emoticons, strings of symbols imitating body language. Today the use of emoticons in online conversation adds values to the facilitation of the online communication process in e-mails, instant messaging applications or blogs [1]. Now a days web provides a way to produce large volume of opinions by allowing people to express their opinion on various social networking sites like Twitter, Facebook [1].…”

“…Today the use of emoticons in online conversation adds values to the facilitation of the online communication process in e-mails, instant messaging applications or blogs [1]. Now a days web provides a way to produce large volume of opinions by allowing people to express their opinion on various social networking sites like Twitter, Facebook [1]. Finding the sentiment or kind of reaction of the people within the tweet is important for planning the marketing strategies [2].…”