Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social Media User Geolocation

Geolocating social media users aims to discover the real geographical locations of users from their publicly available data,which can support online location-based applications such as disaster alerts and local content recommen-dations.Social relationship-based methods represent a classical approach for geolocating social media.However,geographically proximate relationships are sparse and challenging to discern within social networks,thereby affecting the accuracy of user geolocation.To address this challenge,we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence(NGSI)to improve geolocation accuracy.Firstly,we propose a method for evaluating the homophily of locations based on the k-order neighbor-hood geographic distribution(k-NGD)similarity among users.There are notable differences in the distribution of k-NGD similarity between location-proximate and non-location-proximate users.Exploiting this distinction,we filter out non-location-proximate social relationships to enhance location homophily in the social network.To better utilize the location-proximate relationships in social networks,we propose a graph neural network algorithm based on the social structure influence.The algorithm enables us to perform a weighted aggregation of the information of users’multi-hop neighborhood,thereby mitigating the over-smoothing problem of user features and improving user geolocation performance.Experimental results on real social media dataset demonstrate that the neighborhood geographical distribution similarity metric can effectively filter out non-location-proximate social relationships.Moreover,compared with 7 existing social relationship-based user positioning methods,our proposed method can achieve multi-granularity user geolocation and improve the accuracy by 4.84%to 13.28%.

A Study on the Influence of Social Media Use on Psychological Anxiety among Young Women

To explore the relationship between social influence,social comparison,clarity of self-concept,and psychological anxiety among young women during their usage of social networking sites,our study selected 338 young women aged 14-34 from the social site platforms of Little Red Book and Weibo for questionnaire surveys.The Passive Social Network Utilization Scale,Social Comparison Scale(SCS),Social Influence Questionnaire,Self-Concept Clarity Scale(SCCS),and Generalized Anxiety Disorder Scale(GAD-7)were employed to measure the subjects.Our results show that the frequency of passive social media use is positively related to the level of psychological anxiety.Social comparison,social influence,and unclear self-concepts under social media use are negatively predictive of psychological anxiety.The chain mediation effects indicate that social comparison and social influence under social media use negatively predict the clarity of self-concept,thus having a negative impact on the psychological health of young women.Therefore,young women should strengthen their self-concepts,control their frequency of social media usage,avoid addiction,and pay special attention to their frequency of passive use,in order to protect their psychological health.Our study provides some practical implications and insights regarding the relationship between young women’s social media use and psychological health.

From Social Media to Ballot Box:Leveraging Location-Aware Sentiment Analysis for Election Predictions

Predicting election outcomes is a crucial undertaking,and various methods are employed for this purpose,such as traditional opinion polling,and social media analysis.However,traditional polling approaches often struggle to capture the intricate nuances of voter sentiment at local levels,resulting in a limited depth of analysis and understanding.In light of this challenge,this study focuses on predicting elections at the state/regional level along with the country level,intending to offer a comprehensive analysis and deeper insights into the electoral process.To achieve this,the study introduces the Location-Based Election Prediction Model(LEPM),which utilizes social media data,specifically Twitter,and integrates location-aware sentiment analysis techniques at both the state/region and country levels.LEPM predicts the support and opposing strength of each political party/candidate.To determine the location of users/voters who have not disclosed their location information in tweets,the model utilizes a Voter Location Detection(VotLocaDetect)approach,which leverages recent tweets/posts.The sentiment analysis techniques employed in this study include rule-based sentiment analysis,Valence Aware Dictionary and Sentiment Reasoner(VADER)as well as transformers-based sentiment analysis such as Bidirectional Encoder Representations from Transformers(BERT),BERTweet,and Election based BERT(ElecBERT).This study uses the 2020 United States(US)Presidential Election as a case study.By applying the LEPM model to the election,the study demonstrates its ability to accurately predict outcomes in forty-one states,achieving an 0.84 accuracy rate at the state level.Moreover,at the country level,the LEPM model outperforms traditional polling results.With a low Mean Absolute Error(MAE)of 0.87,the model exhibits more precise predictions and serves as a successful alternative to conventional polls and other methodologies.Leveraging the extensive social media data,the LEPM model provides nuanced insights into voter behavior,enabling policymakers to make informed decisions and facilitating in-depth analyses of elections.The study emphasizes the importance of using social media data for reliable election prediction and offers implications for enhancing prediction accuracy and understanding voter sentiment and behavior.

The Media Images of Old Influencers on TikTok:A Multimodal Critical Discourse Analysis

Drawing on the insights from multimodal critical discourse analysis,this study mainly focuses on two super-gerontic celebrities by selecting 60 videos to elucidate how their images are represented through linguistic(e.g.,captions,and hashtags)and other semiotic resources(e.g.,accessories,semiotic tools,and etc.).The findings suggest that images of the old celebrities are characterized as being attractive,wise,stylish,healthy and young,indicating that they are breaking up the stereotypical images of old people who are unattractive,dependent and senile.The phenomenon of old influencers making themselves visible on the social media suggests that they are moving towards successful aging with the backdrop of aging society in China.This present study suggests that multimodal construction of old celebrities can inform relevant practice to combat ageism in the media and helps to empower the old people in the media discourse.In doing so,the pedagogical implication of present study lies in its education about how we view aging in the aging society.

Media Influence Over the Transformation of Stigma Toward Depression in Japan

in Japan, the number of depression patients has markedly increased over the last 10 years, and depression is now a major social concern. Moreover, there are concerns that patients with depression are not always seeking the treatment they need, in part due to the stigma associated with the illness. Despite of increasing public awareness of depression, the stigma has not lessened, but has changed in form. Previous studies report that depression which was once viewed as a special psychiatric illness is now viewed as a ＂common＂ mental illness. The author, too, believes that the nature of the stigmatization has changed in recent years to become more complex and ultimately continues to present a barrier to treatment for people with depression. This study aims to explore how the stigmatization has changed by examining one specific aspect in society that may have contributed to this change, namely, the media＇s portrayal of depression. The author presents and discusses clear examples of how the Japanese media＇s portrayals of depression have changed, particularly over the last 20 to 30 years, and discusses how media influence could have contributed to the shifts in stigmatization, with reference to labeling theory and growing social isolation.

Who should you be following? The top 100 social media influencers in orthopaedic surgery

BACKGROUND Social media has been credited with the potential to transform medicine,and Twitter was recently named“an essential tool”for the academic surgeon.Despite this,peer-to-peer and educational influence on social media has not been studied within orthopaedic surgery.This knowledge is important to identify who is controlling the conversation about orthopaedics to the public.We hypothesized that the plurality of top influencers would be sports medicine surgeons,that social media influence would not be disconnected from academic productivity,and that some of the top social media influencers in orthopaedic surgery would not be orthopaedic surgeons.AIM To identify the top 100 social media influencers within orthopaedics,characterize who they are,and relate their social media influence to academic influence.METHODS Twitter influence scores for the topic“orthopaedics”were collected in July 2018 using Right Relevance software.The accounts with the top influence scores were linked to individual names,and the account owners were characterized with respect to specialty,subspecialty,practice setting,location,board certification,and academic Hirsch index(h-index).RESULTS Seventy-eight percent of top influencers were orthopaedic surgeons.The most common locations included California(13%),Florida(8%),New York(7%),United Kingdom(7%),Colorado(6%),and Minnesota(6%).The mean academic h-index of the top influencers(n=79)was 13.67±4.12(mean±95%CI)and median 7(range 1-89)(median reported h-index of academic orthopaedic faculty is 5 and orthopaedic chairpersons is 13).Of the 78 orthopaedic surgeons,the most common subspecialties were sports medicine(54%),hand and upper extremity(18%),and spine(8%).Most influencers worked in private practice(53%),followed by academics(17%),privademics(14%),and hospital-based(9%).All eligible orthopaedic surgeons with publicly-verifiable board certification statuses were board-certified(n=74).CONCLUSION The top orthopaedic social media influencers on Twitter were predominantly board-certified,sports-medicine subspecialists working in private practice in the United States.Social media influence was highly concordant with academic productivity as measured by the academic h-index.Though the majority of influencers are orthopaedic surgeons,22%of top influencers on Twitter are not,which is important to identify given the potential for these individuals to influence patients’perceptions and expectations.This study also provides the top influencer network for other orthopaedic surgeons to engage with on social media to improve their own social media influence.

A Study on Media Culture＇s Negative Influence on Children

The link between media culture and its real world effect has been a hot topic for many years. Many people believe that media have an obviously bad effect on children. More than 1000 studies conducted in the past 40 years show that excessive exposure to media violence causes the violent behavior in real life. Some other researches prove that media contain heavy messages that promote unhealthy habits or antisocial behaviors. This might be true. However, people often overstate the effects of media on children. Media are not the only elements that can lead to children＇s violence, antisocial behavior and bad habits. Other factors, like society, parents, communities, can also influence their behavior. In fact, if we can control the exposure to media in moderation, our children can benefit a lot from media culture.

A Brief Analysis of the Influence of Online Media on Fashion Design

The 21 st century is a time of digitization and infurmationization. Online media have been going forward rapidly and have penetrated into various aspects of people＇ s life, thus having a significant impact on people＇ s production and life. Under such circumstance, traditional fashion indnstry has also been influenced by online media and has gradually transformed to digitalization. Fashion design is likely to get away from simplex manual design and to transform to the design method of man-machine synergy. The introduction of network technique into fashion design will bring vast potential for future development of fashion design.

A Cumulative Proportional Odds Model to Analyze the Influence of Mass Media on Teenagers in Messina

The media are constantly evolving at a breakneck pace and mainly young people, with their flexibility of mind and their continuous curiosity, can better understand the characteristics and potential of such advances. The aim of this paper is to analyze the relationship between teenagers and media, in order to try to better understand the habits and to conduct analysis on social interactions with young people. In order to evaluate the influence of mass media in the life of the young people, the Statisticians of Messina University decided to perform a statistical survey to evaluate the influence of the media in the life of Messina＇s teenagers. A questionnaire entitled ＂Perceptions of the influence exerted by mass media＂ was administered in some schools. From the methodological point of view, three statistical models were estimated in order to formalize the dependence of the mass media influence by the kind of TV programs, the time spent on TV viewing and computer use and the kind of most used social networks. Since the mass media influence is an ordinal variable expressed by four ordered categories （1 = nothing; 2 = low; 3 = average; 4 = high） we used the Cumulative Proportional Odds Model to formalize the dependence by the potential predictors.

The Impact of Short Media Videos on Urban Tourism Marketing:Taking Zibo and Xi'an as Examples

In the era of new media,short videos as an innovative means of communication have led to significant changes in the promotion strategies of tourist cities.The prosperity of the tourism industry has a significant driving effect on local economic growth,and marketing strategies are the key to the progress of the tourism industry.Through efficient marketing methods,the visibility of tourist attractions and cities can be significantly improved,thereby attracting more tourists and injecting new vitality into the local tourism industry and the overall economy.At present,with the rapid development of short video platforms such as TikTok and the sharp increase in the number of users,short video marketing has gradually received widespread attention from industry professionals and the general public.Some cities have achieved good results in tourism marketing implemented with the help of short video platforms,prompting more cities to use short videos for marketing activities.However,short videos also negatively impact urban tourism marketing,reducing the appeal of TikTok marketing to audiences.Therefore,this article conducts in-depth research on the impact of short video media on urban tourism marketing,elaborates on the advantages,analyzes the impact,proposes strategies for the application,and hopes to provide a reference for cities to use short videos for tourism marketing.

Improving Sentiment Analysis in Election-Based Conversations on Twitter with ElecBERT Language Model

Sentiment analysis plays a vital role in understanding public opinions and sentiments toward various topics.In recent years,the rise of social media platforms(SMPs)has provided a rich source of data for analyzing public opinions,particularly in the context of election-related conversations.Nevertheless,sentiment analysis of electionrelated tweets presents unique challenges due to the complex language used,including figurative expressions,sarcasm,and the spread of misinformation.To address these challenges,this paper proposes Election-focused Bidirectional Encoder Representations from Transformers(ElecBERT),a new model for sentiment analysis in the context of election-related tweets.Election-related tweets pose unique challenges for sentiment analysis due to their complex language,sarcasm,andmisinformation.ElecBERT is based on the Bidirectional Encoder Representations from Transformers(BERT)language model and is fine-tuned on two datasets:Election-Related Sentiment-Annotated Tweets(ElecSent)-Multi-Languages,containing 5.31 million labeled tweets in multiple languages,and ElecSent-English,containing 4.75million labeled tweets in English.Themodel outperforms othermachine learning models such as Support Vector Machines(SVM),Na飗e Bayes(NB),and eXtreme Gradient Boosting(XGBoost),with an accuracy of 0.9905 and F1-score of 0.9816 on ElecSent-Multi-Languages,and an accuracy of 0.9930 and F1-score of 0.9899 on ElecSent-English.The performance of differentmodels was compared using the 2020 United States(US)Presidential Election as a case study.The ElecBERT-English and ElecBERT-Multi-Languages models outperformed BERTweet,with the ElecBERT-English model achieving aMean Absolute Error(MAE)of 6.13.This paper presents a valuable contribution to sentiment analysis in the context of election-related tweets,with potential applications in political analysis,social media management,and policymaking.

The Impact of Social Media on Mental Health:Finding an Antidote for the Anxiety Era

Social media has become an inseparable part of modern life,but concerns have arisen regarding its influence on mental health.This article aims to delve into the intricate relationship between social media and mental health,highlighting both the benefits it brings and the risks it poses.Drawing upon existing research,this study reveals that excessive reliance on social media can contribute to mental health issues such as anxiety and depression,social isolation,and the spread of violent or hateful speech.Therefore,individuals need to be mindful of these potential hazards and take measures to protect their mental well-being.Through a comprehensive analysis of the positive and negative effects of social media on mental health,this article puts forward practical solutions to alleviate any adverse consequences.For instance,individuals are encouraged to use social media moderately,cultivate healthy digital habits,and limit their screen time.Moreover,governments and society as a whole should actively promote mental health awareness and reinforce regulations around social media usage to minimize potential negative impacts.In conclusion,while social media brings convenience and various benefits,it cannot be ignored that it also has the potential to impact mental health.By recognizing and addressing the associated risks,individuals,governments,and society can work together to foster a culture of healthy social media practices and safeguard mental well-being.The innovative approaches proposed in this article serve as a helpful guide for further exploration in this intriguing field.

Remote Influence Tactics

Research into social influence theory has been extensive and has repeatedly shown the power that influence tactics exert over individuals in an organization. Despite the extant conceptualizations of political influence tactics in organizations, very little research has focused on how these tactics play out for organizations implementing more autonomous team settings, whose interactions are not proximally located close to one another. By extending social influence theory to the inclusion of media synchronicity theory, this research contributes insight into how political influence tactics may operate across a variety of media in organizations employing remote work structures. A conceptual model of remote influence tactics is developed and the implications are discussed as part of this research agenda.

Women Political Candidates The Malaysian Media and Their Concerns

Globally, women now play a key role in economic, political, and social cultural affairs, and Malaysia is no exception. Equitable representation by women in the political arena is viewed as crucial in the improvement of women＇s participation in the decision-making process. Nevertheless, though women have made and make great contributions in both the private and public spheres, a review of media＇s coverage of women in the public realm shows a strong tendency to relegate women to mainly domestic affairs. This is consistent with findings from studies on women political candidates＇ image during campaign issues that showed that though women candidates attempted to present themselves in decisive and assertive ways, gender stereotyping was dominant in the media agenda and persistent biases typical of traditional gender representations in the media prevailed. There is very little research in Malaysia on how the media frames women candidates during campaign periods, or what issues are aligned with women candidates. The construction of images of women political candidates, in particular, is often omitted in most research on the General Election. This study analyses how women candidates were covered in selected Malaysian newspapers in the 2008 General Election. The types of issues women political candidates are identified with in the newspapers are also analysed.

Evaluating Third-Person Effects Among Foreigners on China’s Social Media:Wechat and Tantan as Case Study

The social media have become part of the daily lives of foreigners living in China as they try to cope with social cultural dynamics of their environment. They rely on social media to keep in touch with loved ones, make new friends, and keep in touch with news and information around the world. To many of them, the social media are a necessary tool in managing boredom. However, the use of the social media comes with the challenge of third-person effect (TPE), a hypothesis which holds that individuals believe media have more effects on others than they have on themselves. Using two of the leading social media apps in China, Wechat and Tantan, by using a survey approach, we investigated the manifestation of TPE among foreigners in China who are members of the selected social media communities. Our results confirm TPE among our study group. It also shows that those under the influence of TPE have the potential for social media addiction. We advise that social media users are conscious of TPE in view of its negative effects on their well-being.

I’m Nervous about Sharing This Secret with You:Youtube Influencers Generate Strong Parasocial Interactions by Discussing Personal Issues

Purpose:Performers may generate loyalty partly through eliciting illusory personal connections with their audience,parasocial relationships(PSRs),and individual illusory exchanges,parasocial interactions(PSIs).On social media,semi-PSIs are real but imbalanced exchanges with audiences,including through comments on influencers’videos,and strong semi-PSIs are those that occur within PSRs.This article introduces and assesses an automatic method to detect videos with strong PSI potential.Design/methodology/approach:Strong semi-PSIs were hypothesized to occur when commenters used a variant of the pronoun“you”,typically addressing the influencer.Comments on the videos of UK female influencer channels were used to test whether the proportion of you pronoun comments could be an automated indicator of strong PSI potential,and to find factors associating with the strong PSI potential of influencer videos.The highest and lowest strong PSI potential videos for 117 influencers were classified with content analysis for strong PSI potential and evidence of factors that might elicit PSIs.Findings:The you pronoun proportion was effective at indicating video strong PSI potential,the first automated method to detect any type of PSI.Gazing at the camera,head and shoulders framing,discussing personal issues,and focusing on the influencer associated with higher strong PSI potential for influencer videos.New social media factors found include requesting feedback and discussing the channel itself.Research limitations:Only one country,genre and social media platform was analysed.Practical implications:The method can be used to automatically detect YouTube videos with strong PSI potential,helping influencers to monitor their performance.Originality/value:This is the first automatic method to detect any aspect of PSI or PSR.

Digital Influencer's choice of product endorsement:A perspective of congruence

To infer product fitness information,consumers often consult digital influencers who exert effort to learn and evaluate product features and then propagate information to their followers.However,influencers'recommendations are not limited to products that exactly match their expertise,which may lead followers to unfollow them.This study investigates which product(high or low congruence)an influencer should endorse and how much endorsement effort should be exerted.Using a theoretical model,we obtain several interesting results.First,endorsing a low-congruence product can surprisingly benefit the influencer if the penalty per lost follower is moderate or if the influencer has sufficiently high efficiency in reducing the perception error of this product.Second,although the influencer has high expertise in the high-congruence product,she will lose more followers when endorsing it than when endorsing the low-congruence product if a particularly small or large proportion of her followers are potential consumers of the low-congruence product.Third,when the influencer endorses the low-congruence product,the number of new followers increases with the size of the influencer's follower base only when the follower base is small and a large proportion of followers are potential consumers of the low-congruence product.Interestingly,as the size of the follower base increases,the influencer always exerts more effort when endorsing the high-congruence product but will exert less effort in learning about the low-congruence product if a sufficiently small proportion of followers are potential consumers.Finally,after taking consumers'knowledge about product features into account,the main results still hold,and when considering the competition between influencers,we uncover the conditions under which both influencers will choose to endorse the high-congruence product.

大学生社交媒体信息安全风险感知影响因素

文章提出社交媒体信息安全风险感知影响因素关系假设,以大学生社交媒体用户群体为研究对象,通过问卷调研风险感知现状,在构建结构方程模型的基础上对问卷数据进行了模型验证和中介效应检验。研究发现:大学生社交媒体信息安全风险感知程度的城乡间差距明显,其面对信息安全风险主要采用系统式处理;媒体信任度、社会群体归属感、卷入认知会对系统式处理产生影响,知识和信息有效性会对启发式-系统式处理产生影响;系统式处理在知识、媒体信任度、社会群体归属感、卷入认知、信息有效性和风险感知之间起完全中介效应,负面情绪直接正向影响风险感知。

中国形象的“他塑”:“洋网红”对海外受众认知、情感和行为的影响——基于YouTube视频受众评论的分析

“洋网红”在海外讲述中国故事的现象日益引起关注,他们具备讲述中国故事的“主体间性”,被认为是中国形象“他塑”的组成部分,能够为中国故事的国际传播提供新的可能性。“洋网红”主要使用YouTube平台发布视频,受众观看视频后的评论则直接反映“洋网红”讲述中国故事的传播效果。通过对视频内容和受众评论的分析,发现“洋网红”视频使受众在认知层面产生符号的交融,一定程度上能避免东方主义,改善海外受众对华的刻板印象;在情感层面,对于与社会问题、时事相关的视频,受众容易对视频内容和制作动机产生“对抗式解读”,而对于语言搞笑类、美食文化类视频,受众则基于共通情感实现对话;观看视频后,受众在评论区联结成基于“趣缘”的“微社群”,在互动中对视频内容进行延展,产生了学习中文或游览中国等线下行动意向。作为跨文化的讲述者,“洋网红”拥有双重文化背景和文化身份,具有较为显著且区别于中国本土传播者的优势,可以弱化信息生产者和接收者在意识形态和文化背景方面存在的错位,有效帮助海外受众降低文化折扣、消除认知偏差和误解,对中国形象建构有着较好的“他塑”作用。但与此同时,“洋网红”的特殊身份也具有一定风险,因而需要对其生产的内容进行适度引导和把关。