Personality Traits for Egyptian Twitter Users Dataset

Salem, Marwa S.; Ismail, Sally; Aref, Mostafa

doi:10.1145/3328833.3328851

Cited by 23 publications

(18 citation statements)

References 15 publications

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“…Along with the text feature, several numerical features with an absolute correlation value higher than 0.05 were employed. Compared with the baseline model in [14], the best binary model improved by 3.0%, while the best multiclass model improved by 6.7%.…”

Section: Related Work 21 Personality Detection From Arabic Languagementioning

confidence: 93%

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A hybrid approach based on personality traits for hate speech detection in Arabic social media

Elzayady

Mohamed

Badran

et al. 2023

IJECE

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<p>In recent years, as social media has grown in popularity, people have gained the ability to freely share their views. However, this may lead to users' conflict and hostility, resulting in unattractive online environments. Hate speech relates to using expressions or phrases that are violent, offensive, or insulting to a minority of people. The number of Arab social media users is quickly rising, and this is being followed by an increase in the frequency of cyber hate speech in the area. Therefore, the automated detection of Arabic hate speech has become a major concern for many stakeholders. The intersection of personality learning and hate speech detection is a relatively less studied niche. We suggest a novel approach that is focused on extracting personality trait features and using these features to detect Arabic hate speech. The experimental results show that the proposed approach is superior in terms of the macro-F1 score by achieving 82.3% compared to previous work reported in the literature.</p>

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Section: Related Work 21 Personality Detection From Arabic Languagementioning

confidence: 93%

“…Salem et al [14] proposed a machine learning method for predicting the personalities of Arabic users' Twitter accounts. They published a new Twitter-based personality traits dataset called (AraPersonality) for the Egyptian dialect.…”

Section: Related Work 21 Personality Detection From Arabic Languagementioning

confidence: 99%

A hybrid approach based on personality traits for hate speech detection in Arabic social media

Elzayady

Mohamed

Badran

et al. 2023

IJECE

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“…They extracted main feature 2000 most frequent character trigrams as input to SMO. Marwa et al [16] used tf-idf for n-grams as features to four machine learning algorithm. These algorithms are SVM, Multinomial Naïve Bayes (MNB), KNN and decision tree.…”

Section: Related Workmentioning

confidence: 99%

“…These algorithms are SVM, Multinomial Naïve Bayes (MNB), KNN and decision tree. For more details, a fully detailed review can be found in [16].…”

Section: Related Workmentioning

confidence: 99%

Preprocessing the Egyptian Arabic Dialect for Personality Traits Prediction

salim

Saad

Aref

2019

IJICIS

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Each individual has his own distinct character, making his own decisions which is based on his personality. Researchers in computer science field have tried to reach a model for extracting personality traits relying on user's profiles on social network sites as an input. Content created by users such as text posts, photos and shared activities in social network sites are considered as a huge source of data. Regarding user-created text, it has been proved that text pre-processing has a great impact if was applied to text before using it in research. In this paper, the effect of pre-processing (stemming and stop word removal) and adding numerical features is tested on the performance of Arabic personality prediction using AraPersonality dataset, which yielded 3.0% and 6.7% overall improvement to baseline experiments in binary representation and multiclass representation respectively.

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“…Therefore, mining and studying this Big Data of conversations from Twitter has been of significant interest to the research community. In the last few years, there have been several works in the fields of Big Data, Data Mining, and Natural Language Processing related to the development of datasets of Twitter conversations related to different topics, technologies, events, diseases, viruses, etc., such as -movies [38], COVID-19 [39], elections [40], toxic behavior amongst adolescents [41], music [42], natural hazards [43], personality traits [44], civil unrest [45], drug safety [46], climate change [47], hate speech [48], migration patterns [49], conspiracy theories [50], and Inflammatory Bowel Disease [51], just to name a few. Recent studies [52][53][54] have shown that sharing such data helps in the advancement of research, improves the quality of innovation, supports better investigation, and helps to avoid redundant efforts.…”

Section: Introductionmentioning

confidence: 99%

Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets and 100 Research Questions

Thakur

2022

SSRN Journal

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Personality Traits for Egyptian Twitter Users Dataset

Cited by 23 publications

References 15 publications

A hybrid approach based on personality traits for hate speech detection in Arabic social media

A hybrid approach based on personality traits for hate speech detection in Arabic social media

Preprocessing the Egyptian Arabic Dialect for Personality Traits Prediction

Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets and 100 Research Questions

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