@inproceedings{hakami-etal-2022-context,
title = "A Context-free {A}rabic Emoji Sentiment Lexicon ({CF}-{A}rab-{ESL})",
author = "Hakami, Shatha Ali A. and
Hendley, Robert and
Smith, Phillip",
editor = "Al-Khalifa, Hend and
Elsayed, Tamer and
Mubarak, Hamdy and
Al-Thubaity, Abdulmohsen and
Magdy, Walid and
Darwish, Kareem",
booktitle = "Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.osact-1.6",
pages = "51--59",
abstract = "Emoji can be valuable features in textual sentiment analysis. One of the key elements of the use of emoji in sentiment analysis is the emoji sentiment lexicon. However, constructing such a lexicon is a challenging task. This is because interpreting the sentiment conveyed by these pictographic symbols is highly subjective, and differs depending upon how each person perceives them. Cultural background is considered to be one of the main factors that affects emoji sentiment interpretation. Thus, we focus in this work on targeting people from Arab cultures. This is done by constructing a context-free Arabic emoji sentiment lexicon annotated by native Arabic speakers from seven different regions (Gulf, Egypt, Levant, Sudan, North Africa, Iraq, and Yemen) to see how these Arabic users label the sentiment of these symbols without a textual context. We recruited 53 annotators (males and females) to annotate 1,069 unique emoji. Then we evaluated the reliability of the annotation for each participant by applying sensitivity (Recall) and consistency (Krippendorff{'}s Alpha) tests. For the analysis, we investigated the resulting emoji sentiment annotations to explore the impact of the Arabic cultural context. We analyzed this cultural reflection from different perspectives, including national affiliation, use of colour indications, animal indications, weather indications and religious impact.",
}
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<abstract>Emoji can be valuable features in textual sentiment analysis. One of the key elements of the use of emoji in sentiment analysis is the emoji sentiment lexicon. However, constructing such a lexicon is a challenging task. This is because interpreting the sentiment conveyed by these pictographic symbols is highly subjective, and differs depending upon how each person perceives them. Cultural background is considered to be one of the main factors that affects emoji sentiment interpretation. Thus, we focus in this work on targeting people from Arab cultures. This is done by constructing a context-free Arabic emoji sentiment lexicon annotated by native Arabic speakers from seven different regions (Gulf, Egypt, Levant, Sudan, North Africa, Iraq, and Yemen) to see how these Arabic users label the sentiment of these symbols without a textual context. We recruited 53 annotators (males and females) to annotate 1,069 unique emoji. Then we evaluated the reliability of the annotation for each participant by applying sensitivity (Recall) and consistency (Krippendorff’s Alpha) tests. For the analysis, we investigated the resulting emoji sentiment annotations to explore the impact of the Arabic cultural context. We analyzed this cultural reflection from different perspectives, including national affiliation, use of colour indications, animal indications, weather indications and religious impact.</abstract>
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%0 Conference Proceedings
%T A Context-free Arabic Emoji Sentiment Lexicon (CF-Arab-ESL)
%A Hakami, Shatha Ali A.
%A Hendley, Robert
%A Smith, Phillip
%Y Al-Khalifa, Hend
%Y Elsayed, Tamer
%Y Mubarak, Hamdy
%Y Al-Thubaity, Abdulmohsen
%Y Magdy, Walid
%Y Darwish, Kareem
%S Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur’an QA and Fine-Grained Hate Speech Detection
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F hakami-etal-2022-context
%X Emoji can be valuable features in textual sentiment analysis. One of the key elements of the use of emoji in sentiment analysis is the emoji sentiment lexicon. However, constructing such a lexicon is a challenging task. This is because interpreting the sentiment conveyed by these pictographic symbols is highly subjective, and differs depending upon how each person perceives them. Cultural background is considered to be one of the main factors that affects emoji sentiment interpretation. Thus, we focus in this work on targeting people from Arab cultures. This is done by constructing a context-free Arabic emoji sentiment lexicon annotated by native Arabic speakers from seven different regions (Gulf, Egypt, Levant, Sudan, North Africa, Iraq, and Yemen) to see how these Arabic users label the sentiment of these symbols without a textual context. We recruited 53 annotators (males and females) to annotate 1,069 unique emoji. Then we evaluated the reliability of the annotation for each participant by applying sensitivity (Recall) and consistency (Krippendorff’s Alpha) tests. For the analysis, we investigated the resulting emoji sentiment annotations to explore the impact of the Arabic cultural context. We analyzed this cultural reflection from different perspectives, including national affiliation, use of colour indications, animal indications, weather indications and religious impact.
%U https://aclanthology.org/2022.osact-1.6
%P 51-59
Markdown (Informal)
[A Context-free Arabic Emoji Sentiment Lexicon (CF-Arab-ESL)](https://aclanthology.org/2022.osact-1.6) (Hakami et al., OSACT 2022)
ACL
- Shatha Ali A. Hakami, Robert Hendley, and Phillip Smith. 2022. A Context-free Arabic Emoji Sentiment Lexicon (CF-Arab-ESL). In Proceedinsg of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks on Qur'an QA and Fine-Grained Hate Speech Detection, pages 51–59, Marseille, France. European Language Resources Association.