Emoji Classification using Random Forest Classifier

Madhu Bala; Meenu Gupta; Rakesh Kumar

doi:10.1109/icac3n56670.2022.10074460

Emoji Classification using Random Forest Classifier

Madhu Bala
, Meenu Gupta
, Rakesh Kumar

Chandigarh University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The automatic classification of emotions based on emojis is used in several applications such as social media platforms like Twitter are able to communicate their thoughts on a subject. Emojis are visual symbols that are used to express feelings and emotions on social media. This paper will address the development of an automated learning model that allows the classification of emotions in emojis and small texts in English using Bag of Words (BoW), Ngrams, and VADER sentiment scores. Further emoji images are processed with Gabor wavelet to get the features for training with a Random Forest (RF) classifier. To obtain different emotions, different emoji images are further classified using an RF classifier. The suggested technique achieves 94.59% classification accuracy.

Original language	English
Title of host publication	Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022
Editors	Vishnu Sharma, Vishnu Sharma, Manjeet Singh, Manjeet Singh, Jaya Sinha
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	728-732
Number of pages	5
ISBN (Electronic)	9781665474368
DOIs	https://doi.org/10.1109/icac3n56670.2022.10074460
State	Published - 2022
Externally published	Yes
Event	4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022 - Greater Noida, India Duration: 16 Dec 2022 → 17 Dec 2022

Publication series

Name	Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022

Conference

Conference	4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022
Country/Territory	India
City	Greater Noida
Period	16/12/22 → 17/12/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

BOW
Emoji
RF
Sentiment Analysis
VADER

Access to Document

10.1109/icac3n56670.2022.10074460

Cite this

Bala, M., Gupta, M., & Kumar, R. (2022). Emoji Classification using Random Forest Classifier. In V. Sharma, V. Sharma, M. Singh, M. Singh, & J. Sinha (Eds.), Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022 (pp. 728-732). (Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icac3n56670.2022.10074460

Bala, Madhu ; Gupta, Meenu ; Kumar, Rakesh. / Emoji Classification using Random Forest Classifier. Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022. editor / Vishnu Sharma ; Vishnu Sharma ; Manjeet Singh ; Manjeet Singh ; Jaya Sinha. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 728-732 (Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022).

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title = "Emoji Classification using Random Forest Classifier",

abstract = "The automatic classification of emotions based on emojis is used in several applications such as social media platforms like Twitter are able to communicate their thoughts on a subject. Emojis are visual symbols that are used to express feelings and emotions on social media. This paper will address the development of an automated learning model that allows the classification of emotions in emojis and small texts in English using Bag of Words (BoW), Ngrams, and VADER sentiment scores. Further emoji images are processed with Gabor wavelet to get the features for training with a Random Forest (RF) classifier. To obtain different emotions, different emoji images are further classified using an RF classifier. The suggested technique achieves 94.59\% classification accuracy.",

keywords = "BOW, Emoji, RF, Sentiment Analysis, VADER",

author = "Madhu Bala and Meenu Gupta and Rakesh Kumar",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022 ; Conference date: 16-12-2022 Through 17-12-2022",

year = "2022",

doi = "10.1109/icac3n56670.2022.10074460",

language = "אנגלית",

series = "Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "728--732",

editor = "Vishnu Sharma and Vishnu Sharma and Manjeet Singh and Manjeet Singh and Jaya Sinha",

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address = "ארצות הברית",

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Bala, M, Gupta, M & Kumar, R 2022, Emoji Classification using Random Forest Classifier. in V Sharma, V Sharma, M Singh, M Singh & J Sinha (eds), Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022. Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022, Institute of Electrical and Electronics Engineers Inc., pp. 728-732, 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022, Greater Noida, India, 16/12/22. https://doi.org/10.1109/icac3n56670.2022.10074460

Emoji Classification using Random Forest Classifier. / Bala, Madhu; Gupta, Meenu; Kumar, Rakesh.
Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022. ed. / Vishnu Sharma; Vishnu Sharma; Manjeet Singh; Manjeet Singh; Jaya Sinha. Institute of Electrical and Electronics Engineers Inc., 2022. p. 728-732 (Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Gupta, Meenu

AU - Kumar, Rakesh

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AB - The automatic classification of emotions based on emojis is used in several applications such as social media platforms like Twitter are able to communicate their thoughts on a subject. Emojis are visual symbols that are used to express feelings and emotions on social media. This paper will address the development of an automated learning model that allows the classification of emotions in emojis and small texts in English using Bag of Words (BoW), Ngrams, and VADER sentiment scores. Further emoji images are processed with Gabor wavelet to get the features for training with a Random Forest (RF) classifier. To obtain different emotions, different emoji images are further classified using an RF classifier. The suggested technique achieves 94.59% classification accuracy.

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A2 - Sharma, Vishnu

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Y2 - 16 December 2022 through 17 December 2022

ER -

Bala M, Gupta M, Kumar R. Emoji Classification using Random Forest Classifier. In Sharma V, Sharma V, Singh M, Singh M, Sinha J, editors, Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 728-732. (Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022). doi: 10.1109/icac3n56670.2022.10074460

Emoji Classification using Random Forest Classifier

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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