This study examined the processing of emotional facial expression of emoticon compared to those of human. With pictures of emoticon faces and human faces expressing happy, angry, fearful, and neutral emotions along with pictures of houses and scrambled faces, 24 participants were required to do location-judgment about two gaps on contour of facial and control stimuli (non-attention) or were req...

In this paper, we introduce Haptic-Emoticon, which is used in a text message. It expresses a writer’s emotion and/or decorates the message with physical stimulus on a reader’s skin. We employ stroking motions for that purpose. The motions are represented as a 2D trajectory so that a writer can create the Haptic-Emoticon with a conventional pointing input device. The input line is recorded as an...

This paper describes the development of an emoticon recommendation systembased on users’ emotional statements. In order to develop this system, an innovative emoticon database consisting of a table of emoticons with points expressed from each of 10 distinctive emotions was created. An evaluation experiment showed that our proposed system achieved an improvement of 28.1 points over a baseline sy...

Emoticons in informal text communication are common worldwide. They have the potential to reveal emotion and social functions, analogous to facial expression and body gestures in face-to-face verbal communication. Our findings from a corpus study of online text communication by a group of scientists, some of whom were bilingual and others monolingual, suggested that patterns of emoticon use dep...

Japanese emoticons are widely used to express users’ feelings and intentions in social media, blogs and instant messages. Japanese smartphone keypads have a feature that shows a list of emoticons, enabling users to insert emoticons simply by touching them. However, this list of emoticons contains more than 200, which is difficult to choose from, so a method to reorder the list and recommend app...

Tweet sentiment classification seeks to identify the emotional polarity of a tweet. One potential way to enhance classification performance is to include emoticons as features. Emoticons are representations of faces expressing various emotions in text. They are created through combinations of letters, punctuation marks and symbols, and are frequently found within tweets. While emoticons have be...

This paper shows the connection between emoticons and politeness in written computer-mediated communication. It studies if there are some differences in the use of emoticon between Czech and English written tweets. The assumptions about the use of emoticons were based on the use of greetings and thanks in real, faceto-face situations. The first assumption, that welcome greeting phrase would be ...

In recent years, Twitter Sentiment Analysis (TSA) has become a hot research topic. The target of this task is to analyse the sentiment polarity of the tweets. There are a lot of machine learning methods specifically developed to solve TSA problems, such as fully supervised method, distantly supervised method and combined method of these two. Considering the specialty of tweets that a limitation...

This paper presents CAO, a system for affect analysis of emoticons. Emoticons are strings of symbols widely used in text-based online communication to convey emotions. It extracts emoticons from input and determines specific emotions they express. Firstly, by matching the extracted emoticons to a raw emoticon database, containing over ten thousand emoticon samples extracted from the Web and ann...

Recent studies report that using green labels to denote healthier foods, and red to denote less healthy foods increases consumption of green- and decreases consumption of red-labelled foods. Other symbols (e.g. emoticons conveying normative approval and disapproval) could also be used to signal the healthiness and/or acceptability of consuming such products. The present study tested the combine...