While affect plays a similar fundamental role in both, electronic and face-to-face negotiations, the expression of emotions in computer-mediated communication differs considerably from face-to-face settings. The aim of this experimental study is to analyze how the systematic use of emoticons – facilitated with software – affects negotiation behavior in alternative computermediated negotiation s...

Emoticons seem to enrich computer-mediated communication by improving enjoyment, perceived richness and usefulness of information (Huang, Yen, & Zhang, 2008). Despite their extensive use over the last decades, the way emoticons affect subsequent emotional/cognitive processing is not fully understood. Here we conducted a masked priming experiment that explored the time course of the masked affec...

Emoticons are pictorial/textual depictions of facial expressions used in marketing communications. Little is known about how customers interpret positive or negative emoticons by customer service employees failure contexts. We investigate the impact emoticon type on satisfaction and re-purchasing intention, examine sequential mediating role perceived sincerity willingness to forgive. Results sh...

Emoticons have been widely used in Computer mediated communication (CMC) such as Instant Messenger (IM). This study investigates the effect of communication task, interpersonal perception, and relationship intimacy on the use of emoticons in IM. The results show that task formality and two aspects of interpersonal perception affect the emoticon usage. Detailed discussions and implications are a...

Online writing lacks the non-verbal cues present in face-toface communication, which provide additional contextual information about the utterance, such as the speaker’s intention or affective state. To fill this void, a number of orthographic features, such as emoticons, expressive lengthening, and non-standard punctuation, have become popular in social media services including Twitter and Ins...

This study investigated the effect of story-based technique, L1 translation, and Whatsapp emoticon puzzle solving on EFL learners’ learning proverbs. From among 90 female intermediate level learners at two language institutes in Qom, Iran, 60 homogeneous students were chosen following the administration of a sample of Nelson proficiency test and a pre-test. The 60 participants were then assigne...

Twitter sentiment analysis (TSA) has become a hot research topic in recent years. The goal of this task is to discover the attitude or opinion tweets, which typically formulated as machine learning based text classification problem. Some methods use manually labeled data train fully supervised models, while others some noisy labels, such emoticons and hashtags, for model training. In general, w...