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The study aims to examine the effects of social media activities on stock prices of the energy sector. In this respect, the sample covers the monthly period from 2015m6 to 2020m5 has been observed. Energy stocks as S&P 500 index (SP), stock market volatility index (VIX), trade-weighted USD index (USD), and Brent oil prices (OIL) have been used as independent variables. Accordingly, three different models have been created to analyze the link between returns, volatility and trading volume and Twitter sentiments by using Augmented Mean Group. As a result, we found that Twitter sentiment values have no significant impact on the returns and volatility of the companies. Tweets, on the other hand, appear to have a favorable impact on company trading volume values.
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http://dx.doi.org/10.1007/s11356-022-21269-9 | DOI Listing |
Afr J Prim Health Care Fam Med
September 2025
Department of Optometry, Faculty of Health Sciences, University of the Free State, Bloemfontein.
Background: Social media has become a platform where unheard voices within different communities are shared with government.
Aim: The study explored and described expressed reactions of social media users regarding the implementation of the National Health Insurance (NHI) in South Africa.
Setting: This study was conducted online on existing social media platforms that share current news.
JMIR Infodemiology
August 2025
Faculty of Medicine, University of Lleida, Lleida, Spain.
Background: The internet and social media have been considered useful platforms for obtaining health information. However, critical and erroneous content about vaccines on social media has been associated with vaccination delays and refusal.
Objective: This study aimed to examine how social networks influence access to and perceptions of vaccine-related information.
Sci Rep
August 2025
College of Engineering and Technology, Department of Computer Science, Dilla University, Po. Box 419, Dilla, Ethiopia.
Opinion mining is more challenging than it was before because of all the user-generated material on social media. People use Twitter (X) to gather opinions on products, advancements, and laws. Sentiment Analysis (SA) examines people's thoughts, feelings, and views on numerous topics.
View Article and Find Full Text PDFJ Med Internet Res
August 2025
Edson College of Nursing and Health Innovation, Arizona State University, 500 N 3rd St, Phoenix, Phoenix, AZ, 85004, United States, 1 (330) 272-4294.
Background: HIV remains a global challenge, with stigma, financial constraints, and psychosocial barriers preventing people living with HIV from accessing health care services, driving them to seek information and support on social media. Despite the growing role of digital platforms in health communication, existing research often narrowly focuses on specific HIV-related topics rather than offering a broader landscape of thematic patterns. In addition, much of the existing research lacks large-scale analysis and predominantly predates COVID-19 and the platform's transition to X (formerly known as Twitter), limiting our understanding of the comprehensive, dynamic, and postpandemic HIV-related discourse.
View Article and Find Full Text PDFPLoS One
August 2025
Biocomputing and Developmental Systems (BDS) Research Group, University of Limerick, Limerick, Ireland.
The analysis of Arabic Twitter data sets is a highly active research topic, particularly since the outbreak of COVID-19 and subsequent attempts to understand public sentiment related to the pandemic. This activity is partially driven by the high number of Arabic Twitter users, around 164 million. Word embedding models are a vital tool for analysing Twitter data sets, as they are considered one of the essential methods of transforming words into numbers that can be processed using machine learning (ML) algorithms.
View Article and Find Full Text PDF