Grammatical Errors in Social Media Caption

Yuliah, Siti; Purnamasari, Yessy; Yunita, Elsa

doi:10.15640/ijll.v8n2a3

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…The third reason for the choice of this approach laid in the lack of numeric data that is generated from a Moroccan context following a quantitative approach. A lot of recent studies that investigated the relationship between social media and the development of grammar in a certain population like Andrade & Andersen, (2020), Yuliah et al, (2020), Lumban Tobing & Pranowo, (2020) and Aniasih et al, (2022) to name a few, relied on approaches that were either mixed methods or a qualitative in nature. Scholars were mostly interested in the attitudes of students in relation to their grammatical development and social media.…”

Section: Methodsmentioning

confidence: 99%

Investigating the Relationship between Students’ L2 Grammar Competence and Social Media Use

Laabidi,

Ouahbi

2023

jllce

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Social media has been gaining popularity in the educational sector recently. Whether scholars support its educational use because of its benefits or whether they reject its use because of the stigma surrounding it, the use of social media has become quite a trend in the educational field. This study investigated the use of social media in relation to the grammatical competence of third year Moulay Ismail University, school of arts and humanities’ English department students. The two variables in question in this study were investigated quantitatively through the use of a survey that consisted of; first a grammatical test to test the students’ grammatical competence and second some statements that students had to answer; the statements were based on a 5 scale Likert scale. The findings of this study showed that the use of social media does influence the grammatical competence of Moroccan learners. Moreover, the different statistical tests proved that the two variables have a significant relationship.

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Section: Methodsmentioning

confidence: 99%

Investigating the Relationship between Students’ L2 Grammar Competence and Social Media Use

Laabidi,

Ouahbi

2023

jllce

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“…Notably, omission errors emerged as the most prevalent, comprising 78% of the identified grammatical errors. Beyond academic settings, Yuliah et al (2020), as well as Sihotang et al (2021), explored grammatical errors in social media captions, specifically on Instagram. These studies identified weaknesses in caption writing, highlighting a broader need for investigating such errors in various online contexts.…”

Section: Introductionmentioning

confidence: 99%

Analyzing grammar errors among Hellotalk users and proposing effective correction strategies

Arifin,

Heriyanto,

Kurniadi

et al. 2024

englie

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HelloTalk is a popular social media platform where users from diverse linguistic backgrounds converge to communicate and improve their second language (L2) skills. This study focuses on grammatical errors made by users on the HelloTalk app during English interactions. Employing the observation method. Employing a qualitative approach, the study conducted a comprehensive analysis of 357 instances across 280 posts, showcasing a nuanced understanding of the challenges faced by users in their language learning journey. The identified strategies for addressing these errors encompasses several ways such as providing corrective feedback (CF), categorizing errors, utilizing language learning apps for English, and implementing a systematic approach to monitoring and tracking progress. The study's findings provided valuable insights for educators, language learners, and app developers, offering a basis for targeted interventions. Additionally, future research may explore integrating emerging technologies like artificial intelligence and natural language processing to enhance error correction efficiency and personalized feedback on language learning platforms.

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“…Undoubtedly, English is the widely spoken language in the world (Crystal, 2008). But as there are no hardbound rules that users must text in English, the text found on social media could be multilingual and lack grammatical rules (Yuliah et al, 2020). Also, there could be unwanted symbols in the text .…”

Section: Introductionmentioning

confidence: 99%

Hypers at ComMA@ICON: Modelling Aggressiveness, Gender Bias and Communal Bias Identification

Benhur¹,

Nayak²,

Sivanraju³

et al. 2021

Preprint

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Due to the exponentially increasing reach of social media, it is essential to focus on its negative aspects as it can potentially divide society and incite people into violence. In this paper, we present our system description of work on the shared task ComMA@ICON, where we have to classify how aggressive the sentence is and if the sentence is gender-biased or communal-biased.These three could be the primary reasons to cause significant problems in society. As team Hypers we have proposed an approach which utilizes different pretrained models with Attention and mean pooling methods. We were able to get Rank 3 with 0.223 Instance F1 score on Bengali, Rank 2 with 0.322 Instance F1 score on Multi-lingual set, Rank 4 with 0.129 Instance F1 score on Meitei and Rank 5 with 0.336 Instance F1 score on Hindi. The source code and the pretrained models of this work can be found here 1 .

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Grammatical Errors in Social Media Caption

Cited by 3 publications

References 3 publications

Investigating the Relationship between Students’ L2 Grammar Competence and Social Media Use

Investigating the Relationship between Students’ L2 Grammar Competence and Social Media Use

Analyzing grammar errors among Hellotalk users and proposing effective correction strategies

Hypers at ComMA@ICON: Modelling Aggressiveness, Gender Bias and Communal Bias Identification

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