Gao, Yankun Xie, Zidian Li, Dongmei
Published in
JMIR public health and surveillance
Previous studies have shown that electronic cigarette (e-cigarette) users might be more vulnerable to COVID-19 infection and could develop more severe symptoms if they contract the disease owing to their impaired immune responses to viral infections. Social media platforms such as Twitter have been widely used by individuals worldwide to express th...
Ortiz Espinoza, Ángeles Espejel Trujillo, Angelina
Twitter as a means for promoting opinions has not gone unnoticed by political agents. This study looks at the Twitter messages of the candidates for the Presidency of Mexico in the 2018 elections and reviews their contents, the reactions they produced, and whether they were interpreted positively or negatively. The hypothesis, which our research su...
Liu, Ruixue Xiao, Jing
Published in
International Journal of Environmental Research and Public Health
It is essential to give full consideration to the potential barriers facing urban parks from their better functions and meeting residents’ needs in terms of collective perception and satisfaction. This paper presents the methods of using social media (Dianping) data to investigate the potential factors affecting people’s satisfaction with urban par...
Pota, Marco Ventura, Mirko Catelli, Rosario Esposito, Massimo
Published in
Sensors (Basel, Switzerland)
Over the last decade industrial and academic communities have increased their focus on sentiment analysis techniques, especially applied to tweets. State-of-the-art results have been recently achieved using language models trained from scratch on corpora made up exclusively of tweets, in order to better handle the Twitter jargon. This work aims to ...
Lee, Min-Joon Lee, Tae-Ro Lee, Seo-Joon Jang, Jin-Soo Kim, Eung Ju
Published in
Frontiers in Psychiatry
The Sewol Ferry Disaster which took place in 16th of April, 2014, was a national level disaster in South Korea that caused severe social distress nation-wide. No research at the domestic level thus far has examined the influence of the disaster on social stress through a sentiment analysis of social media data. Data extracted from YouTube, Twitter,...
Valdez, Danny ten Thij, Marijn Bathina, Krishna Rutter, Lauren A Bollen, Johan
Published in
Journal of Medical Internet Research
Background The COVID-19 pandemic led to unprecedented mitigation efforts that disrupted the daily lives of millions. Beyond the general health repercussions of the pandemic itself, these measures also present a challenge to the world’s mental health and health care systems. Considering that traditional survey methods are time-consuming and expensiv...
Sadiq, Amin Muhammad Ahn, Huynsik Choi, Young Bok
Published in
Sensors (Basel, Switzerland)
A rapidly increasing growth of social networks and the propensity of users to communicate their physical activities, thoughts, expressions, and viewpoints in text, visual, and audio material have opened up new possibilities and opportunities in sentiment and activity analysis. Although sentiment and activity analysis of text streams has been extens...
Berkovic, Danielle Ackerman, Ilana N Briggs, Andrew M Ayton, Darshini
Published in
Journal of medical Internet research
Emerging evidence suggests that people with arthritis are reporting increased physical pain and psychological distress during the COVID-19 pandemic. At the same time, Twitter's daily usage has surged by 23% throughout the pandemic period, presenting a unique opportunity to assess the content and sentiment of tweets. Individuals with arthritis use T...
Xie, Runbin Chu, Samuel Kai Wah Chiu, Dickson Kak Wah Wang, Yangshu
Published in
Data and Information Management
It is necessary and important to understand public responses to crises, including disease outbreaks. Traditionally, surveys have played an essential role in collecting public opinion, while nowadays, with the increasing popularity of social media, mining social media data serves as another popular tool in opinion mining research. To understand the ...
Chang, Angela Schulz, Peter Johannes Tu, ShengTsung Liu, Matthew Tingchi
Published in
Journal of medical Internet research
Information about a new coronavirus emerged in 2019 and rapidly spread around the world, gaining significant public attention and attracting negative bias. The use of stigmatizing language for the purpose of blaming sparked a debate. This study aims to identify social stigma and negative sentiment toward the blameworthy agents in social communities...
