Tweets on a horror movie: An investigation into relationships between sentiment strength, cognitive language and tweet virality DOI
Ling Zhang, Xiangming Mu

Journal of Information Science, Journal Year: 2022, Volume and Issue: 50(5), P. 1085 - 1097

Published: Aug. 29, 2022

This article studies how sentiment strength and cognitive language may influence the levels of tweet virality. A total 11,381 tweets about a horror movie (‘Mother!’) were collected. Based on definitions two independent variables: use, dependent variable: virality, data descriptive statistics analysis variance (ANOVA) applied to reveal relationships between virality factors. The results indicate that high is associated with either lower level or/and higher use by statistically significant margin. finding more evident for negative tweets. study findings help improve understanding sentimental factors impacting guide industry marketing content achieve social media. conclusions can also be other industries, government agencies, organisations individuals who intend quickly disseminate specific information media platforms.

Language: Английский

Sentiment Analysis of Twitter Data DOI Creative Commons
Yili Wang,

Jiaxuan Guo,

Chengsheng Yuan

et al.

Applied Sciences, Journal Year: 2022, Volume and Issue: 12(22), P. 11775 - 11775

Published: Nov. 19, 2022

Twitter has become a major social media platform and attracted considerable interest among researchers in sentiment analysis. Research into Sentiment Analysis (TSA) is an active subfield of text mining. TSA refers to the use computers process subjective nature data, including its opinions sentiments. In this research, thorough review most recent developments area, wide range newly proposed algorithms applications are explored. Each publication arranged category based on significance particular type method. The purpose survey provide concise, nearly comprehensive overview techniques related fields. primary contributions detailed classifications numerous articles depiction current direction research field TSA.

Language: Английский

Citations

64
AI-driven social media text analysis during crisis: A review for natural disasters and pandemics DOI
Junaid Abdul Wahid, Mingliang Xu, Muhammad Ayoub

et al.

Applied Soft Computing, Journal Year: 2025, Volume and Issue: 171, P. 112774 - 112774

Published: Jan. 31, 2025

Language: Английский

Citations

1
Investigating the COVID-19 vaccine discussions on Twitter through a multilayer network-based approach DOI Open Access
Gianluca Bonifazi, Bernardo Breve, Stefano Cirillo

et al.

Information Processing & Management, Journal Year: 2022, Volume and Issue: 59(6), P. 103095 - 103095

Published: Sept. 12, 2022

Language: Английский

Citations

38
The effect of fear and situational motivation on online information avoidance: The case of COVID-19 DOI
Tahmina Sultana, Gurpreet Dhillon, Tiago Oliveira

et al.

International Journal of Information Management, Journal Year: 2022, Volume and Issue: 69, P. 102596 - 102596

Published: Nov. 18, 2022

Language: Английский

Citations

29
Multimodal negative sentiment recognition of online public opinion on public health emergencies based on graph convolutional networks and ensemble learning DOI
Ziming Zeng, Shouqiang Sun, Qingqing Li

et al.

Information Processing & Management, Journal Year: 2023, Volume and Issue: 60(4), P. 103378 - 103378

Published: April 9, 2023

Language: Английский

Citations

21
How does government microblog affect tourism market value? The perspective of signaling theory DOI

Hongzhi Zhu,

Fang Wang

Information Processing & Management, Journal Year: 2022, Volume and Issue: 59(4), P. 102991 - 102991

Published: June 10, 2022

Language: Английский

Citations

18
A term function–aware keyword citation network method for science mapping analysis DOI
Jiamin Wang,

Qikai Cheng,

Wei Lu

et al.

Information Processing & Management, Journal Year: 2023, Volume and Issue: 60(4), P. 103405 - 103405

Published: May 12, 2023

Language: Английский

Citations

9
Exploring public sentiment and vaccination uptake of COVID-19 vaccines in England: a spatiotemporal and sociodemographic analysis of Twitter data DOI Creative Commons
Tao Cheng,

Baoyan Han,

Yunzhe Liu

et al.

Frontiers in Public Health, Journal Year: 2023, Volume and Issue: 11

Published: Aug. 17, 2023

Vaccination is widely regarded as the paramount approach for safeguarding individuals against repercussions of COVID-19. Nonetheless, concerns surrounding efficacy and potential adverse effects these vaccines have become prevalent among public. To date, there has been a paucity research investigating public perceptions adoption COVID-19 vaccines. Therefore, present study endeavours to address this lacuna by undertaking spatiotemporal analysis sentiments towards vaccination its uptake in England at local authority level, while concurrently examining sociodemographic attributes national level.A sentiment Twitter data was undertaken delineate distribution positive their demographic correlates. Positive were categorized into clusters streamline comparison across different age gender demographics. The relationship between evaluated using Spearman's correlation coefficient. Additionally, bivariate carried out further probe rates.The results indicated that majority tweets posted males, although females expressed higher levels sentiment. group over 40 dominated exhibited highest polarity. positively correlated with number level.Overall, opinions on are predominantly positive. receiving vaccinations level prevalence attitudes vaccines, particularly population aged 40. These findings suggest targeted efforts increase younger populations, necessary achieve widespread coverage.

Language: Английский

Citations

7
A Review of Deep Learning Models for Twitter Sentiment Analysis: Challenges and Opportunities DOI
Laxmi Chaudhary, Nancy Girdhar, Deepak Kumar Sharma

et al.

IEEE Transactions on Computational Social Systems, Journal Year: 2023, Volume and Issue: 11(3), P. 3550 - 3579

Published: Oct. 27, 2023

Microblogging site Twitter (re-branded to X since July 2023) is one of the most influential online social media websites, which offers a platform for masses communicate, expresses their opinions, and shares information on wide range subjects products, resulting in creation large amount unstructured data. This has attracted significant attention from researchers who seek understand analyze sentiments contained within this massive user-generated text. The task sentiment analysis (SA) entails extracting identifying user opinions text, various lexicon-and machine learning-based methods have been developed over years accomplish this. However, deep learning (DL)-based approaches recently become dominant due superior performance. study briefs standard preprocessing techniques word embeddings data preparation. It then delves into taxonomy provide comprehensive summary DL-based approaches. In addition, work compiles popular benchmark datasets highlights evaluation metrics employed performance measures resources available public domain aid SA tasks. Furthermore, survey discusses domain-specific practical applications Finally, concludes with research challenges outlines future outlooks further investigation.

Language: Английский

Citations

6
The impact of COVID-19 anxiety on the academic motivation, life-orientation, and meaning in life of university students DOI Creative Commons
Ryan Francis O. Cayubit

Discover Psychology, Journal Year: 2024, Volume and Issue: 4(1)

Published: Nov. 18, 2024

Despite the formal declaration of end global health emergency related to COVID-19, disease continues pose significant challenges worldwide. This study addresses gap in existing literature regarding impact COVID-19 anxiety on university students during peak pandemic. Specifically, it examined how influenced meaning life, life orientation, and academic motivation; variables that are known predictors student success their overall well-being. Conducted as a non-experimental quantitative cross-sectional study, data were collected from 557 participants selected through purposive sampling. The research used Coronavirus Pandemic Anxiety Scale, Academic Motivation Revised Life Orientation Test, Meaning Questionnaire gather relevant data. Findings reveal has negative influence motivation, presence meaning, orientation. results also indicate positive relationship between search for life. These findings not only enhance understanding pandemic's adverse impacts but provide basis future interventions strategies by educational stakeholders policymakers aimed at mitigating these effects.

Language: Английский

Citations

1