scholarly journals Social Media Behavior and Emotional Evolution during Emergency Events

Healthcare ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1109
Author(s):  
Mingyun Gu ◽  
Haixiang Guo ◽  
Jun Zhuang
Keyword(s):  
Social Media ◽  
Online Social Networks ◽  
User Behavior ◽  
Social Emotional ◽  
Critical Function ◽  
Sina Weibo ◽  
Emergency Event ◽  
Social Media Platforms ◽  
New Perspective ◽  
The Impact

Online social networks have recently become a vital source for emergency event news and the consequent venting of emotions. However, knowledge on what drives user emotion and behavioral responses to emergency event developments are still limited. Therefore, unlike previous studies that have only explored trending themes and public sentiment in social media, this study sought to develop a holistic framework to assess the impact of emergency developments on emotions and behavior by exploring the evolution of trending themes and public sentiments in social media posts as a focal event developed. By examining the event timelines and the associated hashtags on the popular Chinese social media site Sina-Weibo, the 2019 Wuxi viaduct collapse accident was taken as the research object and the event timeline and the Sina-Weibo tagging function focused on to analyze the behaviors and emotional changes in the social media users and elucidate the correlations. It can conclude that: (i) There were some social media rules being adhered to and that new focused news from the same event impacted user behavior and the popularity of previous thematic discussions. (ii) While the most critical function for users appeared to express their emotions, the user foci changed when recent focus news emerged. (iii) As the news of the collapse deepened, the change in user sentiment was found to be positively correlated with the information released by personal-authentication accounts. This research provides a new perspective on the extraction of information from social media platforms in emergencies and social-emotional transmission rules.

scholarly journals Concerns Expressed by Chinese Social Media Users During the COVID-19 Pandemic: Content Analysis of Sina Weibo Microblogging Data (Preprint)

2020 ◽  
Author(s):  
Junze Wang ◽  
Ying Zhou ◽  
Wei Zhang ◽  
Richard Evans ◽  
Chengyan Zhu
Keyword(s):  
Social Media ◽  
Latent Dirichlet Allocation ◽  
Vaccine Development ◽  
User Behavior ◽  
Chinese Government ◽  
Web Crawler ◽  
Health Crisis ◽  
User Behavior Analysis ◽  
Sina Weibo ◽  
Social Media Platforms

BACKGROUND The COVID-19 pandemic has created a global health crisis that is affecting economies and societies worldwide. During times of uncertainty and unexpected change, people have turned to social media platforms as communication tools and primary information sources. Platforms such as Twitter and Sina Weibo have allowed communities to share discussion and emotional support; they also play important roles for individuals, governments, and organizations in exchanging information and expressing opinions. However, research that studies the main concerns expressed by social media users during the pandemic is limited. OBJECTIVE The aim of this study was to examine the main concerns raised and discussed by citizens on Sina Weibo, the largest social media platform in China, during the COVID-19 pandemic. METHODS We used a web crawler tool and a set of predefined search terms (<i>New Coronavirus Pneumonia</i>, <i>New Coronavirus</i>, and <i>COVID-19</i>) to investigate concerns raised by Sina Weibo users. Textual information and metadata (number of likes, comments, retweets, publishing time, and publishing location) of microblog posts published between December 1, 2019, and July 32, 2020, were collected. After segmenting the words of the collected text, we used a topic modeling technique, latent Dirichlet allocation (LDA), to identify the most common topics posted by users. We analyzed the emotional tendencies of the topics, calculated the proportional distribution of the topics, performed user behavior analysis on the topics using data collected from the number of likes, comments, and retweets, and studied the changes in user concerns and differences in participation between citizens living in different regions of mainland China. RESULTS Based on the 203,191 eligible microblog posts collected, we identified 17 topics and grouped them into 8 themes. These topics were pandemic statistics, domestic epidemic, epidemics in other countries worldwide, COVID-19 treatments, medical resources, economic shock, quarantine and investigation, patients’ outcry for help, work and production resumption, psychological influence, joint prevention and control, material donation, epidemics in neighboring countries, vaccine development, fueling and saluting antiepidemic action, detection, and study resumption. The mean sentiment was positive for 11 topics and negative for 6 topics. The topic with the highest mean of retweets was domestic epidemic, while the topic with the highest mean of likes was quarantine and investigation. CONCLUSIONS Concerns expressed by social media users are highly correlated with the evolution of the global pandemic. During the COVID-19 pandemic, social media has provided a platform for Chinese government departments and organizations to better understand public concerns and demands. Similarly, social media has provided channels to disseminate information about epidemic prevention and has influenced public attitudes and behaviors. Government departments, especially those related to health, can create appropriate policies in a timely manner through monitoring social media platforms to guide public opinion and behavior during epidemics.

scholarly journals Concerns Expressed by Chinese Social Media Users During the COVID-19 Pandemic: Content Analysis of Sina Weibo Microblogging Data

10.2196/22152 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e22152
Author(s):  
Junze Wang ◽  
Ying Zhou ◽  
Wei Zhang ◽  
Richard Evans ◽  
Chengyan Zhu
Keyword(s):  
Social Media ◽  
Latent Dirichlet Allocation ◽  
Vaccine Development ◽  
User Behavior ◽  
Chinese Government ◽  
Web Crawler ◽  
Health Crisis ◽  
User Behavior Analysis ◽  
Sina Weibo ◽  
Social Media Platforms

Background The COVID-19 pandemic has created a global health crisis that is affecting economies and societies worldwide. During times of uncertainty and unexpected change, people have turned to social media platforms as communication tools and primary information sources. Platforms such as Twitter and Sina Weibo have allowed communities to share discussion and emotional support; they also play important roles for individuals, governments, and organizations in exchanging information and expressing opinions. However, research that studies the main concerns expressed by social media users during the pandemic is limited. Objective The aim of this study was to examine the main concerns raised and discussed by citizens on Sina Weibo, the largest social media platform in China, during the COVID-19 pandemic. Methods We used a web crawler tool and a set of predefined search terms (New Coronavirus Pneumonia, New Coronavirus, and COVID-19) to investigate concerns raised by Sina Weibo users. Textual information and metadata (number of likes, comments, retweets, publishing time, and publishing location) of microblog posts published between December 1, 2019, and July 32, 2020, were collected. After segmenting the words of the collected text, we used a topic modeling technique, latent Dirichlet allocation (LDA), to identify the most common topics posted by users. We analyzed the emotional tendencies of the topics, calculated the proportional distribution of the topics, performed user behavior analysis on the topics using data collected from the number of likes, comments, and retweets, and studied the changes in user concerns and differences in participation between citizens living in different regions of mainland China. Results Based on the 203,191 eligible microblog posts collected, we identified 17 topics and grouped them into 8 themes. These topics were pandemic statistics, domestic epidemic, epidemics in other countries worldwide, COVID-19 treatments, medical resources, economic shock, quarantine and investigation, patients’ outcry for help, work and production resumption, psychological influence, joint prevention and control, material donation, epidemics in neighboring countries, vaccine development, fueling and saluting antiepidemic action, detection, and study resumption. The mean sentiment was positive for 11 topics and negative for 6 topics. The topic with the highest mean of retweets was domestic epidemic, while the topic with the highest mean of likes was quarantine and investigation. Conclusions Concerns expressed by social media users are highly correlated with the evolution of the global pandemic. During the COVID-19 pandemic, social media has provided a platform for Chinese government departments and organizations to better understand public concerns and demands. Similarly, social media has provided channels to disseminate information about epidemic prevention and has influenced public attitudes and behaviors. Government departments, especially those related to health, can create appropriate policies in a timely manner through monitoring social media platforms to guide public opinion and behavior during epidemics.

Fuzzy based feature engineering architecture for sentiment analysis of medical discussion over online social networks

2021 ◽  
pp. 1-13
Author(s):  
C S Pavan Kumar ◽  
L D Dhinesh Babu
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Media ◽  
Sentiment Analysis ◽  
Membership Function ◽  
Online Social Networks ◽  
Learning Model ◽  
Feature Engineering ◽  
Machine Learning Model ◽  
Social Media Platforms

Sentiment analysis is widely used to retrieve the hidden sentiments in medical discussions over Online Social Networking platforms such as Twitter, Facebook, Instagram. People often tend to convey their feelings concerning their medical problems over social media platforms. Practitioners and health care workers have started to observe these discussions to assess the impact of health-related issues among the people. This helps in providing better care to improve the quality of life. Dementia is a serious disease in western countries like the United States of America and the United Kingdom, and the respective governments are providing facilities to the affected people. There is much chatter over social media platforms concerning the patients’ care, healthy measures to be followed to avoid disease, check early indications. These chatters have to be carefully monitored to help the officials take necessary precautions for the betterment of the affected. A novel Feature engineering architecture that involves feature-split for sentiment analysis of medical chatter over online social networks with the pipeline is proposed that can be used on any Machine Learning model. The proposed model used the fuzzy membership function in refining the outputs. The machine learning model has obtained sentiment score is subjected to fuzzification and defuzzification by using the trapezoid membership function and center of sums method, respectively. Three datasets are considered for comparison of the proposed and the regular model. The proposed approach delivered better results than the normal approach and is proved to be an effective approach for sentiment analysis of medical discussions over online social networks.

scholarly journals 1414. #Vaccine Twitter Influencers: is it Just About Reach and Followers?

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S714-S715
Author(s):  
Jean-Etienne Poirrier ◽  
Theodore Caputi ◽  
John Ayers ◽  
Mark Dredze ◽  
Sara Poston ◽  
...  
Keyword(s):  
United States ◽  
Social Media ◽  
Standard Deviation ◽  
Small Proportion ◽  
The United States ◽  
Research Support ◽  
Policy Makers ◽  
Media Messages ◽  
Social Media Platforms ◽  
The Impact

Abstract Background A small number of powerful users (“influencers”) dominates conversations on social media platforms: less than 1% of Twitter accounts have at least 3,000 followers and even fewer have hundreds of thousands or millions of followers. Beyond simple metrics (number of tweets, retweets...) little is known about these “influencers”, particularly in relation to their role in shaping online narratives about vaccines. Our goal was to describe influential Twitter accounts that are driving conversations about vaccines and present new metrics of influence. Methods Using publicly-available data from Twitter, we selected posts from 1-Jan-2016 to 31-Dec-2018 and extracted the top 5% of accounts tweeting about vaccines with the most followers. Using automated classifiers, we determined the location of these accounts, and grouped them into those that primarily tweet pro- versus anti-vaccine content. We further characterized the demographics of these influencer accounts. Results From 25,381 vaccine-related tweets available in our sample representing 10,607 users, 530 accounts represented the top 5% by number of followers. These accounts had on average 1,608,637 followers (standard deviation=5,063,421) and 340,390 median followers. Among the accounts for which sentiment was successfully estimated by the classifier, 10.4% (n=55) posted anti-vaccine content and 33.6% (n=178) posted pro-vaccine content. Of the 55 anti-vaccine accounts, 50% (n=18) of the accounts for which location was successfully determined were from the United States. Of the 178 pro-vaccine accounts, 42.5% (n=54) were from the United States. Conclusion This study showed that only a small proportion of Twitter accounts (A) post about vaccines and (B) have a high follower count and post anti-vaccine content. Further analysis of these users may help researchers and policy makers better understand how to amplify the impact of pro-vaccine social media messages. Disclosures Jean-Etienne Poirrier, PhD, MBA, The GSK group of companies (Employee, Shareholder) Theodore Caputi, PhD, Good Analytics Inc. (Consultant) John Ayers, PhD, GSK (Grant/Research Support) Mark Dredze, PhD, Bloomberg LP (Consultant)Good Analytics (Consultant) Sara Poston, PharmD, The GlaxoSmithKline group of companies (Employee, Shareholder) Cosmina Hogea, PhD, GlaxoSmithKline (Employee, Shareholder)

Understanding the Experiences of Anger in the Onset and Progression of Psoriasis: A Qualitative Study Using Social Media (Preprint)

2021 ◽  
Author(s):  
Olivia Hughes ◽  
Rachael Hunter
Keyword(s):  
Social Media ◽  
Qualitative Interviews ◽  
Psychosocial Interventions ◽  
Skin Condition ◽  
Future Research ◽  
Social Media Platforms ◽  
Chronic Skin ◽  
Skin Conditions ◽  
The Impact

BACKGROUND Psoriasis is a chronic inflammatory skin condition, which can be affected by stress. Living with psoriasis can trigger negative emotions, which may influence quality of life. OBJECTIVE This study explored the experiences of people with psoriasis with attention to the potential role of anger in the onset and progression of the chronic skin condition. METHODS Semi-structured qualitative interviews were conducted with twelve participants (n=5 females, n=7 males) recruited online from an advert on a patient charity’s social media platforms. Data were transcribed and analysed using thematic analysis. RESULTS Four key themes were identified: (1) ‘I get really angry with the whole situation:’ anger at the self and others, (2) the impact of anger on psoriasis: angry skin, (3) shared experiences of distress, and (4) moving past anger to affirmation. CONCLUSIONS Findings suggest that anger can have a perceived impact on psoriasis through contributing to sensory symptoms and unhelpful coping cycles and point to a need for enhanced treatment with more psychological support. The findings also highlight the continued stigma which exists for people living with skin conditions and how this may contribute to, and sustain, anger for those individuals. Future research could usefully focus on developing targeted psychosocial interventions to promote healthy emotional coping with psoriasis.

An Experimental Study of Spammer Detection on Chinese Microblogs

2020 ◽  
Vol 30 (11n12) ◽  
pp. 1759-1777
Author(s):  
Jialing Liang ◽  
Peiquan Jin ◽  
Lin Mu ◽  
Jie Zhao
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
User Behavior ◽  
Real Data ◽  
User Profile ◽  
Data Set ◽  
Sina Weibo ◽  
Factors Affecting ◽  
The Government ◽  
Hot Event

With the development of Web 2.0, social media such as Twitter and Sina Weibo have become an essential platform for disseminating hot events. Simultaneously, due to the free policy of microblogging services, users can post user-generated content freely on microblogging platforms. Accordingly, more and more hot events on microblogging platforms have been labeled as spammers. Spammers will not only hurt the healthy development of social media but also introduce many economic and social problems. Therefore, the government and enterprises must distinguish whether a hot event on microblogging platforms is a spammer or is a naturally-developing event. In this paper, we focus on the hot event list on Sina Weibo and collect the relevant microblogs of each hot event to study the detecting methods of spammers. Notably, we develop an integral feature set consisting of user profile, user behavior, and user relationships to reflect various factors affecting the detection of spammers. Then, we employ typical machine learning methods to conduct extensive experiments on detecting spammers. We use a real data set crawled from the most prominent Chinese microblogging platform, Sina Weibo, and evaluate the performance of 10 machine learning models with five sampling methods. The results in terms of various metrics show that the Random Forest model and the over-sampling method achieve the best accuracy in detecting spammers and non-spammers.

scholarly journals Quantifying and contextualizing the impact of bioRxiv preprints through automated social media audience segmentation

2020 ◽  
Author(s):  
Jedidiah Carlson ◽  
Kelley Harris
Keyword(s):  
Social Media ◽  
Video Game ◽  
Research Evaluation ◽  
Right Wing ◽  
Religious Groups ◽  
Audience Segmentation ◽  
Social Media Platforms ◽  
Game Developers ◽  
The Impact ◽  
Media Audience

AbstractEngagement with scientific manuscripts is frequently facilitated by Twitter and other social media platforms. As such, the demographics of a paper’s social media audience provide a wealth of information about how scholarly research is transmitted, consumed, and interpreted by online communities. By paying attention to public perceptions of their publications, scientists can learn whether their research is stimulating positive scholarly and public thought. They can also become aware of potentially negative patterns of interest from groups that misinterpret their work in harmful ways, either willfully or unintentionally, and devise strategies for altering their messaging to mitigate these impacts. In this study, we collected 331,696 Twitter posts referencing 1,800 highly tweeted bioRxiv preprints and leveraged topic modeling to infer the characteristics of various communities engaging with each preprint on Twitter. We agnostically learned the characteristics of these audience sectors from keywords each user’s followers provide in their Twitter biographies. We estimate that 96% of the preprints analyzed are dominated by academic audiences on Twitter, suggesting that social media attention does not always correspond to greater public exposure. We further demonstrate how our audience segmentation method can quantify the level of interest from non-specialist audience sectors such as mental health advocates, dog lovers, video game developers, vegans, bitcoin investors, conspiracy theorists, journalists, religious groups, and political constituencies. Surprisingly, we also found that 10% of the highly tweeted preprints analyzed have sizable (>5%) audience sectors that are associated with right-wing white nationalist communities. Although none of these preprints intentionally espouse any right-wing extremist messages, cases exist where extremist appropriation comprises more than 50% of the tweets referencing a given preprint. These results present unique opportunities for improving and contextualizing research evaluation as well as shedding light on the unavoidable challenges of scientific discourse afforded by social media.

scholarly journals Impact of the COVID-19 Pandemic on Instagram and Influencer Marketing

2021 ◽  
Vol 13 (2) ◽  
pp. 20
Author(s):  
Evelina Francisco ◽  
Nadira Fardos ◽  
Aakash Bhatt ◽  
Gulhan Bizel
Keyword(s):  
Social Media ◽  
Marketing Strategy ◽  
Online Survey ◽  
Video Conferencing ◽  
Marketing Mix ◽  
The Internet ◽  
Exploratory Research ◽  
Social Media Platforms ◽  
The Impact ◽  
Made In

The COVID-19 pandemic and the resulting stay-at-home orders have disrupted all aspects of life globally, most notably our relationship with the internet and social media platforms. People are online more than ever before, working and attending school from home and socializing with friends and family via video conferencing. Marketers and brands have been forced to adapt to a new normal and, as a result, have shifted their brand communication and marketing mix to digital approaches. Hence, this study aims to examine the shift of influencer marketing on Instagram during this period and the possible future implications. By employing an online survey for exploratory research, individuals answered questions addressing their perceptions about the impact of the pandemic, brands and influencers&rsquo; relationship, and the overall changes made in marketing strategy.

scholarly journals A Pilot Study on the Impact of Facebook on Perceptions of Police Force

2019 ◽  
Vol 3 (1) ◽  
pp. 6-11
Author(s):  
Wayne W. L. Chan ◽  
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Public Perception ◽  
Public Discourse ◽  
Police Force ◽  
Online Social Networking ◽  
Individual Interviews ◽  
Social Media Platforms ◽  
Perceptions Of Police ◽  
The Impact

The legal authorities, particularly the police force, have been increasingly facing challenges given the popularity of social media [1, 2]. However, we know very little about how public perceptions of the police are being shaped by social media. In this context, this study attempted to investigate the impact of social media on young people’s perceptions of the police in Hong Kong. The focus of this study was placed on Facebook since it was one of the most popular social media platforms in the city. Facebook was not only conceptualized as a communication medium but also a social networking arena. In this connection, qualitative individual interviews were conducted to explore the online social networking on Facebook and its relation to the perceptions of police force. It was found that the Facebook users who were more likely to stay closely connected with other users with similar views would tend to form the politicized perception of police force. On the other hand, the Facebook users who were to be networked with some other users or real persons with dissimilar views would hold more neutral perceptions of the police. This study was the first of its kind to investigate the role of online social networking in the perceptions of the police, thus filling an important gap in our knowledge of the increasing impact of social media. Therefore, the results of current study were expected to contribute to society by avoiding the disproportionate public discourse about law and order. Keywords: Social Media, Online Social Networking, Public Perception, Police Force.

Investigating the effects of consistent visual identity on social media

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Harsandaldeep Kaur ◽  
Kanwal Roop Kaur
Keyword(s):  
Social Media ◽  
Online Marketing ◽  
Media Environment ◽  
Content Type ◽  
Visual Identity ◽  
Company Reputation ◽  
Social Media Platforms ◽  
Sphere Of Influence ◽  
The Impact ◽  
Practical Implications

Purpose Although the prominence of social media for companies is widely acknowledged, a close examination of the literature reveals a lack of empirical research pertaining to the effect of consistency specifically on social media. Therefore, the purpose of this paper is to fill the gap in social media communication concerning the effect of consistent visual identity on social media users. Design/methodology/approach The study executed an experiment 2 (corporate visual identity condition) × 2 (organization type) between subjects design to map the effects of consistent visual identity on social media users appreciation of the visual identity, attitude toward the company, reputation and intention to commit to a company on social media. Findings The results of the study indicated the significant effects of consistent visual identity on social media users over the inconsistent conditions of visual identity on all dependent variables. Furthermore, there were insignificant main effects of organization type on general judgment, credibility, distinctiveness and reputation of the company. Practical implications This study presents the effects of consistent visual identity on social media platforms. The research will help marketing academicians, graphic designers and social media practitioners in online marketing by using its practical implications to strategically positioning their corporate brand in a social media environment. Originality/value This study provides novel insights on the impact of consistency on social media users. This is the first study to determine the role of consistent visual identity in the social media environment. It thereby adds to the literature of visual identity by developing the sphere of influence of consistency and its effects toward the user’s attitude.

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