Emoji Prediction for Hebrew Political Domain

Liebeskind, Chaya; Liebeskind, Shmuel

doi:10.1145/3308560.3316548

Cited by 17 publications

(5 citation statements)

References 26 publications

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“…Kim et al (2019) developed Reeboc, which can analyze chat content, extract different emotions or topics, and then, based on this, recommend emoji to users. The practice of text-based emoji prediction has also been validated in other languages, such as Hebrew (Liebeskind et al, 2019).…”

Section: Research Fields Regarding Emojimentioning

confidence: 99%

A Systematic Review of Emoji: Current Research and Future Perspectives

et al. 2019

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A growing body of research explores emoji, which are visual symbols in computer mediated communication (CMC). In the 20 years since the first set of emoji was released, research on it has been on the increase, albeit in a variety of directions. We reviewed the extant body of research on emoji and noted the development, usage, function, and application of emoji. In this review article, we provide a systematic review of the extant body of work on emoji, reviewing how they have developed, how they are used differently, what functions they have and what research has been conducted on them in different domains. Furthermore, we summarize directions for future research on this topic.

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Section: Research Fields Regarding Emojimentioning

confidence: 99%

A Systematic Review of Emoji: Current Research and Future Perspectives

et al. 2019

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“…Several studies [16][17][18][19][20][21][22][23][24][25][26] have been dedicated to improving the efficiency of emoticon suggestions. One of these studies, conducted by Pohl et al [17], proposed EmojiZoom, an innovative emoticon input method that surpasses the traditional emoticon keyboards based on long lists.…”

Section: Emoticon Suggestion Systemsmentioning

confidence: 99%

“…This was further investigated through a survey of over 2000 participants by Miller et al [18], who found that text could both increase and decrease the ambiguity of emoticons. Liebeskind et al [23] examined highly sparse n-grams representations and denser character n-grams representations for emoticon classification. Chen et al [24] used emoticon-powered representation learning for crosslingual sentiment classification.…”

Section: Emoticon Suggestion Systemsmentioning

confidence: 99%

Effective Emoticon Suggestion Technique Based on Active Emotional Input Using Facial Expressions and Heart Rate Signals

Kim

Kang

Seo

et al. 2023

Sensors

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The evolution of mobile communication technology has brought about significant changes in the way people communicate. However, the lack of nonverbal cues in computer-mediated communication can make the accurate interpretation of emotions difficult. This study proposes a novel approach for using emotions as active input in mobile systems. This approach combines psychological and neuroscientific principles to accurately and comprehensively assess an individual’s emotions for use as input in mobile systems. The proposed technique combines facial and heart rate information to recognize users’ five prime emotions, which can be implemented on mobile devices using a front camera and a heart rate sensor. A user evaluation was conducted to verify the efficacy and feasibility of the proposed technique, and the results showed that users could express emotions faster and more accurately, with average recognition accuracies of 90% and 82% for induced and intended emotional expression, respectively. The proposed technique has the potential to enhance the user experience and provide more personalized and dynamic interaction with mobile systems.

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“…In addition, their usage patterns allow to predict user characteristics, such as gender [7]. In our context, emoji has been analyzed in political discussion on social networks [25], but only with respect to what representation is best for predicting the emoji to be used in text, regardless of its actual meaning, i.e., the work would be similar in a non-political discussion. Although they are typically understood as emotional or sentiment cues [11], we find that emojis are a powerful predictor of abortion stance in Argentina and Chile, not only in micro-post content, but also in profile elements-mirroring how colored kerchiefs are used in physical manifestations [5,38].…”

Section: Related Workmentioning

confidence: 99%

Every Colour You Are: Stance Prediction and Turnaround in Controversial Issues

Graells-Garrido

Baeza–Yates

Lalmas³

2020

12th ACM Conference on Web Science

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Web platforms have allowed political manifestation and debate for decades. Technology changes have brought new opportunities for expression, and the availability of longitudinal data of these debates entice new questions regarding who participates, and who updates their opinion. The aim of this work is to provide a methodology to measure these phenomena, and to test this methodology on a specific topic, abortion, as observed on one of the most popular micro-blogging platforms. To do so, we followed the discussion on Twitter about abortion in two Spanish-speaking countries from 2015 to 2018. Our main insights are two fold. On the one hand, people adopted new technologies to express their stances, particularly colored variations of heart emojis ( & ) in a way that mirrored physical manifestations on abortion. On the other hand, even on issues with strong opinions, opinions can change, and these changes show differences in demographic groups. These findings imply that debate on the Web embraces new ways of stance adherence, and that changes of opinion can be measured and characterized. CCS CONCEPTS• Human-centered computing → Empirical studies in collaborative and social computing.

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Emoji Prediction for Hebrew Political Domain

Cited by 17 publications

References 26 publications

A Systematic Review of Emoji: Current Research and Future Perspectives

A Systematic Review of Emoji: Current Research and Future Perspectives

Effective Emoticon Suggestion Technique Based on Active Emotional Input Using Facial Expressions and Heart Rate Signals

Every Colour You Are: Stance Prediction and Turnaround in Controversial Issues

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