Genre-based Emoji Usage Analysis and Prediction in Video Comments

Jiang, Hongyu; Ma, Jun

doi:10.1109/dasc-picom-cbdcom-cyberscitech49142.2020.00058

Search citation statements

Order By: Relevance

Paper Sections

Select...

Nonverbal Communication and Emojis1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

2023

Publication Types

Select...

Other2

Article1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

(1 citation statement)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Emoji use has become so widespread that emojis have been applied in other research as a way to endorse or like something, as in online consumer reviews (Huang, Chang, Bilgihan, & Okumus, 2020;Sharma & Dangwal, 2018), and feedback between students and teachers (Dunlap et al, 2016;Moffitt, Padgett, Grieve, 2020). Emojis have even made their way into the development of Artificial Intelligence (Yaswanth & Deepa, 2020;Jiang et al, 2020;Pohl et al, 2017).…”

Section: Nonverbal Communication and Emojismentioning

confidence: 99%

Emoji use in online communication with emerging adults: The impact on ambiguity, affect, and social connection

Losby

View full text Add to dashboard Cite

show abstract

Section: Nonverbal Communication and Emojismentioning

confidence: 99%

Emoji use in online communication with emerging adults: The impact on ambiguity, affect, and social connection

Losby

View full text Add to dashboard Cite

show abstract

Emoji Recommendation System Using Deep Learning Algorithms

Rathod,

Neha,

Purohit

et al. 2023

2023 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

View full text Add to dashboard Cite

Gender and Language Variation on the Comments of Viral Youtube Videos

Cantina¹,

Alvarico²

2022

Spr. J. Arts. Humanit. Soc. Sci.

View full text Add to dashboard Cite

This study aims at analyzing the language variations between female and male comments on YouTube viral videos as to abbreviations, emojis, laughter variants, and spelling variants of personal pronouns, utilizing a mixed-method design. This study revealed that males tend to use abbreviations in their comments in the leisure domain. Females used more abbreviations in the information and knowledge domains and emojis in the two domains. The female users used haha, hehe, and jaja more frequently than male users in the leisure domain. Male and female users used the laughter variant more often in the leisure domain than in the information and knowledge domain. Women preferred to write the standard spelling of the personal pronouns "I" and "you." Moreover, both men and women used abbreviations to express their views immediately to speed up the typing of messages. Women were more familiar with positive and negative emojis than men. Language varies according to YouTube users' preferences in using the language when posting comments online, and the core social attributes influencing language use are social class, social networks, sex and gender, ethnicity, and age. Thus, infographic material with meanings and examples can be distributed to students and teachers.

show abstract

Genre-based Emoji Usage Analysis and Prediction in Video Comments

Cited by 3 publications

References 23 publications

Emoji use in online communication with emerging adults: The impact on ambiguity, affect, and social connection

Emoji use in online communication with emerging adults: The impact on ambiguity, affect, and social connection

Emoji Recommendation System Using Deep Learning Algorithms

Gender and Language Variation on the Comments of Viral Youtube Videos

Contact Info

Product

Resources

About