Combining Linguistic, Semantic and Lexicon Feature for Emoji Classification in Twitter Dataset

Wahyuni, Rinda; Budi, Indra

doi:10.1016/j.procs.2018.08.166

Cited by 7 publications

(8 citation statements)

References 2 publications

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“…It also engages young learners in comprehension of abstract concepts in communication to communicate thoughts, feelings, and positive responses through emoji (Fane, 2017). In the Indonesian context, Wahyuni and Budi (2018) conducted a study focusing on twitter that builds a computational model to classify the emoji to its language features: semantic and lexicon.…”

Section: Mischievous Grimacementioning

confidence: 99%

The Communicative Function of Non-Face Emoji "Folded Hands" in WhatsApp Interaction among Indonesians

Muzakky

Hidayat

Alek

2021

lkw

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This study aimed to examine the communicative functions of the non-face “folded hands” emoji that Indonesians use in WhatsApp interactions. Using descriptive qualitative, the data were analysed through the social semiotic approach proposed by Lemke (1998), the interactional sociolinguistic theory (Gumperz, 1982), and speech act theory. The data were taken from the messages that occurred naturally in several WhatsApp groups. It was re-transcribed and translated in English based on the theory by Dresner and Herring (2010). The findings revealed some functions of the non-face “folded hands” emoji in online communication. At the end of an utterance, it emphasizes message tone, politeness, and soft interaction. Furthermore, rather than this emoji expresses an emotion such as face emoji does, it performs illocutionary forces in communication such as thanking, apologizing, and asking. It is also performed in situational interaction in which the relation of speaker and interlocutor has a formal relation such as teacher-students and leader-staffs. This empirical research added to computer-mediated discourse literature by analyzing the communicative function of folded hands emoji in written discourse. Practically, it might help users interpret the emoji as an abstract concept in the messages.

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Section: Mischievous Grimacementioning

confidence: 99%

The Communicative Function of Non-Face Emoji "Folded Hands" in WhatsApp Interaction among Indonesians

Muzakky

Hidayat

Alek

2021

lkw

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“…Based on previous pre-interviews and studies on emojis commonly used to express positive and negative emotions ( Wahyuni and Budi, 2018 ), we selected a smiley emoji with an open smile and smiling eyes ( ), which is most commonly used in online chats to express positive emotions.…”

Section: Experiments 1: Influence Of Positive Emojis On Initial Online Trust Among College Studentsmentioning

confidence: 99%

Influence of Emojis on Online Trust Among College Students

et al. 2021

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Emojis are increasingly used in online communication and expression, however, most previous studies have focused on describing this phenomenon, but less on how it affects interpersonal trust relationships. Therefore, this study examines the effect of emojis on online interpersonal trust among college students through three experiments. A total of 62 college students were recruited for Experiment 1. The results demonstrated that positive emoji () improved the level of trust of trustors in the trust game [t(60) = –2.79, p = 0.007], whereas that of the control group exerted no effect on the initial level of online trust among college students. Then, 74 college students were selected for Experiment 2. The results indicated no significant differences between the experiment and control groups in terms of the influence of negative emojis () on initial online trust using. A joint analysis (via ANOVA) of Experiments 1 and 2 illustrated that the type of emoji exerted a significant effect [F(2,96) = 3.96, p = 0.02, η2 = 0.08] on college students’ online trust. Finally, we recruited 111 participants for Experiment 3 to explore the role of emojis on online trust among acquaintances. The results suggested that the individual propensity to trust plays a moderate role in the relationship between emojis and online trust among acquaintances. That is, emojis influenced interpersonal trust among acquaintances only if the level of propensity to trust, is low.

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“…Emojis can be represented in different forms depending on the specific task in which they are used. The emoji-based feature extraction can use various syntactical or contextual relations and can use values of different types [19], [21], [37]. For example, they can use binary representation (0 or 1) referring to whether an emoji exists in a particular instance or not, integer numbers such as counting their occurrences in instances, real number such as their existence likelihood or intensities.…”

Section: Representationsmentioning

confidence: 99%

Early and Late Fusion of Emojis and Text to Enhance Opinion Mining

Al-Azani

El-Alfy

2021

IEEE Access

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Opinion mining has gained increasing importance to draw insights from social media content to support decision making. Despite the explosive growth of efforts on linguistic analysis to detect and track people's opinions, more specifically when dealing with aspect-level opinion mining, the results are still away from generalization to real-world applications. Nowadays, emojis are getting excessively popular in social media communication as a complementary way to quickly express opinions and ideas in a visual manner. Two emoji-related issues are highlighted: ambiguity and misinterpretation of emojis' sentiment and tendency of persons to adopt emojis more in positive cases. This paper aims at investigating to what extent the usage of emojis can contribute to the automated detection of sentiment polarity of text messages with focus on Twitter posts in the Arabic language, a widely spoken language but has complex morphology and limited reliable resources for sentiment analysis. For this purpose, after an extensive review of the stateof-the-art of emojis-related work, a dataset is composed and several feature extraction methods are applied for both text and emojis modalities. Moreover, various early and late fusion techniques are proposed to combine both modalities at different levels including feature, score, decision and hybrid. The experimental results revealed that emojis features can significantly improve the classification results, especially when integrated with text at the score level.

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Combining Linguistic, Semantic and Lexicon Feature for Emoji Classification in Twitter Dataset

Cited by 7 publications

References 2 publications

The Communicative Function of Non-Face Emoji "Folded Hands" in WhatsApp Interaction among Indonesians

The Communicative Function of Non-Face Emoji "Folded Hands" in WhatsApp Interaction among Indonesians

Influence of Emojis on Online Trust Among College Students

Early and Late Fusion of Emojis and Text to Enhance Opinion Mining

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