Temporal Impacts of Problematic Social Media Content on Perceived Employee Hirability

Solace in Social Media: Women Unite Under COVID-19

The research is dealt with critical discourse analysis on the politicians' social media posts which is mainly aimed to Investigate the hoax phenomenon especially the content of politicians on the social media posts. The data of the research is taken from the politician status social media through downloading the the pictures, reading the content of pictures carefully, analyzing the hoax posts by using Lynda Walsh (2006), select and identify the hoax posts phenomenon of the politicians' social media posts and to make the data be stronger, the researcher also did an interview with some people and it is acknowledged that the hoax phenomenon of the politicians' social media posts has brought the anxiety in the society life in approaching the presidential election 2019. It has many the power of context that made the society believed on it and to critical the case it is used the theory of Van Djik's framework 1988 and 2001 that focus critical discourse as language, ideology and power.The conclusion of this research is there were many various impacts and the influences toward the society who do not understand in choosing which is a hoax news or a fact news on the social media because in all the pictures of the hoax posts that the researcher put on this thesis, it has proved based on interviewing some people and it has declared by communication and technology that the hoax posts phenomenon that has shared by the society and the politician is really problematic towards the irrational people.

Driven by the need to enhance user traffic on social media (SM) platforms for increasing their advertising revenues, SM platforms are experimenting with new content creation features. However, it is unclear if such initiatives are also beneficial for SM profile owners such as influencers, who are the prime content creators on the SM platforms who use SM posts to build their influence within their network of followers. Our study investigates the effect of introducing one such new SM feature: the “story” on the creation and consumption of SM posts. Leveraging social penetration theory, we hypothesize the influence of introducing story feature on (1) the frequency of SM post creation by profile owners and (2) the extent of follower engagement with SM posts. Employing a quasi-experimental design, we find that the introduction of the story feature reduces the frequency of SM post creation, but the enhanced self-disclosure through the story feature increases follower engagement with the SM posts. However, these effects are moderated by the situating culture of the SM communities: while low-power-distance cultures value profile owners’ self-disclosure, high-power-distance cultures exhibit a mixed influence. Advancing literature on social penetration theory and SM user engagement, our study demonstrates that new self-disclosive SM content creation features do not necessarily benefit all the concerned stakeholders and that the effectiveness of such features might vary from one community to another. Hence, the intended impact of introducing new SM features needs to be carefully evaluated by SM platforms in a holistic manner.

<p><strong><em>The aim</em></strong><em> of the work is to outline the most effective communication channels with residents in smart cities.</em><em></em></p><p><strong><em>Research methodology.</em></strong><em> Both theoretical and empirical research methods were used in the research process. The research methodology consisted of several stages. The first was a comprehensive literature review to understand the current state of knowledge in the fields of smart city development, social media, and urban communication. This involved analyzing existing studies, articles, and reports on how social media is used within smart cities for engaging with residents. The next was data collection. This method was used to build a dataset of types of communication with residents in smart cities. After collecting a dataset of posts in social media, we extract relevant features that can be used to provide effective communication between local authorities and audience. These features include the frequency of writing posts in social media, the types of answers and comments, the explaining of sensitive topics. </em></p><p><strong><em>Results.</em></strong><em> It was found out that effective communication with residents in smart cities should include such features: the use of digital platforms for communication (such as mobile apps, social media, or online forums) have seen increased engagement from residents. This could manifest in higher participation rates in city surveys, community events, or feedback mechanisms. Also it was examined that effective communication channels can lead to higher resident satisfaction. This might be due to quicker responses to complaints, more efficient service delivery, or a greater sense of being heard and considered by city administrations.</em></p><p><strong><em>Novelty.</em></strong><em> The novelty of this work is the proposed effective types of communication with residents in smart cities. For example,</em> <em>younger residents may prefer social media or apps, while older residents might rely on more traditional methods like community newsletters or public meetings. The next studies might also explore how communication technologies impact the social and cultural fabric of urban communities, possibly affecting community bonding, local culture preservation, and social inclusivity.</em></p><p><strong><em>Practical meaning.</em></strong><em> Effective communication channels can lead to higher resident satisfaction. This might be due to quicker responses to complaints, more efficient service delivery, or a greater sense of being heard and considered by city administrations. Moreover, smart city communication strategies might be particularly effective in enhancing public safety. Quick dissemination of information regarding emergencies, health alerts, or public safety incidents can be a significant benefit.</em></p><p><strong><em>Key words:</em></strong><em> social media, communication, audience, smart cities.</em></p>

Background:There is a paucity of information regarding the use of social media by both orthopaedic residents and applicants. Therefore, this investigation aimed to (1) characterize the use of social media by current orthopaedic surgery residents and applicants to an orthopaedic surgery residency and (2) evaluate the influence of social media on applicants to an orthopaedic surgery residency.Methods:An anonymous, nationwide survey was conducted among current orthopaedic surgery residents and fourth-year medical students applying to the authors' orthopaedic surgery. Survey data included demographics, social media usage preferences, social media engagement, and the influence of social media on applicants' perception of and decision to apply to residency programs.Results:Three hundred twelve surveys were completed, which included 170 resident surveys and 142 applicant surveys. Two hundred thirty-seven of the respondents (76%) use social media daily. Two hundred fourteen respondents (72%) have listened to orthopaedic surgery podcasts. Regarding educational social media posts, 81% of the residents and 57% of the applicants preferred case presentations with corresponding imaging; for noneducational posts, 89% of the applicants preferred content involving resident life outside the hospital. When asked how much an orthopaedic residency program's social media presence influenced application decision (on a scale of 0-10, 0 being no influence and 10 being the most influence), the mean response was 3.47 among all respondents.Conclusions:Most survey respondents use social media daily, have listened to orthopaedic podcasts, find case presentations with corresponding imaging the most useful format for educational posts, and prefer to see residency programs post about resident life outside of the hospital. A residency program's social media presence did not significantly influence applicants' decision to apply to a specific program; however, there was a trend toward increasing influence with more recent applicants. Future research should further investigate social media's impact on the residency application process and the influence of social media on orthopaedic applicants and residents.

PurposeOnline influencers are increasingly used by brands around the globe to establish brand communication. This study aims to investigate the characteristics of social media content in terms of presentation style and brand communication among online influencers in China. The authors identified how characteristics of social media posts influence young consumers’ engagement with the posts.Design/methodology/approachThe authors analyzed 1,779 posts from the Sina Weibo accounts of ten top-ranked online influencers by combining traditional content analysis with Web data crawling of audience engagement with social media posts.FindingsOnline influencers in China more frequently used photos than videos to communicate with their social media audience. Altogether 8% and 6% of posts carried information about promotion and event, respectively. Posts with promotional incentives as well as event information were more likely to engage audiences. Altogether 22% of the sampled social media posts mentioned brands. Posts with brand information, however, were less likely to engage audiences. Furthermore, having long text is more effective than photos/images in generating likes from social media audiences.Originality/valueCombining content analysis of social media posts and engagement analytics obtained via Web data crawling, this study is, to the best of the authors’ knowledge, one of the first empirical studies to analyze influencer marketing and young consumers’ reactions to social media in China.

PurposeThe widespread acceptance of various social platforms has increased the number of users posting about various services based on their experiences about the services. Finding out the intended ratings of social media (SM) posts is important for both organizations and prospective users since these posts can help in capturing the user’s perspectives. However, unlike merchant websites, the SM posts related to the service-experience cannot be rated unless explicitly mentioned in the comments. Additionally, predicting ratings can also help to build a database using recent comments for testing recommender algorithms in various scenarios.Design/methodology/approachIn this study, the authors have predicted the ratings of SM posts using linear (Naïve Bayes, max-entropy) and non-linear (k-nearest neighbor, k-NN) classifiers utilizing combinations of different features, sentiment scores and emotion scores.FindingsOverall, the results of this study reveal that the non-linear classifier (k-NN classifier) performed better than the linear classifiers (Naïve Bayes, Max-entropy classifier). Results also show an improvement of performance where the classifier was combined with sentiment and emotion scores. Introduction of the feature “factors of importance” or “the latent factors” also show an improvement of the classifier performance.Originality/valueThis study provides a new avenue of predicting ratings of SM feeds by the use of machine learning algorithms along with a combination of different features like emotional aspects and latent factors.

Nowadays, social media have opened a door in front of us to share individual’s expressions, emotions, and attitudes toward any incident. Sentiment analysis from different social media posts may help us to detect positive, negative, or emotional behavior toward society. Depressive text detection from social media posts is one of the most challenging parts of individual behavior or sentiment analysis. In this paper, different machine learning algorithms are used to detect depressive Bangla text from social media posts. Pre-processing steps like stemming, stop word removal, etc., are used to clean the collected data, and feature extraction techniques like count vectorization, TF-IDF, word embedding, etc., are applied to the collected dataset which consists of 6178 texts collected from social media posts. We have achieved the highest 97% classification accuracy using decision tree and 94% accuracy for bidirectional LSTM (deep learning model) to predict depressive text in Bangla language. Depressive text detection from social media posts will create an opportunity for psychologists to analyze sentiment from shared posts, reactions, and attitudes which may lessen the unwanted activities of the depressed people through diagnosis and taking them under treatment.KeywordsDepressive textBangla languageDeep learningSocial media post

Bu araştırmada, ergenlerin öz-şefkat odağında sosyal medya kullanımına ilişkin görüşleri incelenmiştir. Araştırmanın çalışma grubunu 13-16 yaş arası 26 ergen oluşturmaktadır. Bu araştırmada nitel araştırma yöntemlerinden olgu bilim (fenomenoloji) deseninden yararlanılmıştır. Araştırmanın verileri araştırmacılar tarafından geliştirilen yarı yapılandırılmış görüşme formu ile toplanmıştır. Elde edilen veriler içerik analizi yoluyla çözümlenmiştir. Araştırma bulgularına göre katılımcılar; Instagram, Youtube, Snapcat, Tiktok, Twiter uygulamalarını bir saat ila sekiz saat arasında aktif olarak kullanmaktadır. Ergenlerin sosyal medyayı en sık “ilgi alanlarına yönelik hesapları takip”, “akranların takibi”, “eğlence ve fenomenleri takip” amacı ile kullandıkları görülmüştür. Ergenlerin, sosyal medya takip ettikleri paylaşımlardan mutluluk duymanın yanı sıra paylaşımları gördüklerinde sıklıkla olumsuz hislere kapıldıkları sonucuna ulaşılmıştır. Ergenlerde, sosyal medya paylaşımlarının takibinin ardından dış görünüşünü yetersiz bulmak, arkadaşlarıyla birlikte o paylaşımda yer almayı istemek, özenme, mutsuz hissetme, yaşam şartları ve mali şartları yetersiz hissetmek, moralinin bozulması, kızgın hissetmek temalarının sıkça tekrar ettiği sonucuna ulaşılmıştır. Ergenler bu paylaşımları takip ettiklerinde kendi bedenlerine yönelik eleştiri yaptıklarını ve kendilerini daha az başarılı bulduklarını ifade etmişlerdir. Ergenlerin bir kısmının paylaşım yapmayıp sosyal medyada sadece izleyici olduğu ya da bir ‘private’ hesaptan paylaşım yaptığı bulgusuna ulaşılmıştır. Sosyal medya paylaşımları yüksek oranda beğeni ya da etkileşim almadığında kendilerini üzgün, utanmış, pişman hissettiklerini ve bir kısmı da böyle bir durum karşısında paylaşımı silebileceğini ifade etmiştir. Sosyal medya paylaşımlarına karşı alaycı bir tavırda etkileşim aldıklarında, katılımcıların bir kısmı bu durumu umursamayacağını ifade ederken bir kısmı da üzgün, öfkeli, tedirgin, kinlenmiş, özgüven eksikliği hissetmiş olduklarını ifade etmişlerdir. Ergenlerin bir kısmı fenomenlerin paylaşımlarını izlediğinde kendilerini onlarla kıyaslayabileceğini, bir kısmı ise paylaşımlardan olumsuz etkilenmediğini ifade etmiştir.

Suspended because of social media? Students’ knowledge and opinions of university social media policies and practices

People have done various ways to get information to fulfil their information needs. Until the presence of social media that changes lifestyles, thinking patterns, social society, and education. The presence of Instagram social media is one of the contemporary social media that is of interest to various groups to access information including lectures. This research aims: (1) To describe the motives for using Instagram social media @fuadiainponorogo as information media for FUAD IAIN Ponorogo students class of 2020. (2) To analyse the fulfilment of information needs of FUAD IAIN Ponorogo students class of 2020 on Instagram social media @fuadiainponorogo as information media. The method used is a qualitative descriptive approach. Data analysis using Miles and Hubberman, namely data reduction, data presentation, data verification, and conclusion drawing. Research results: First, the motives for utilising social media Instagram @fuadiainponorogo as information media are four in the MAIN model, namely information arises because of the use of Instagram @fuadiainponorogo as the dissemination of lecture information. Entertainment is seen from posting video reels that follow the trend. Social interaction arises from the interaction between the Instagram account admin @fuadiainponorogo and followers. Personal identity because Instagram account followers @fuadiainponorogo average student Faculty of Ushuluddin, Adab and Da'wah. Second, fulfilling the need for information on the Instagram account @fuadiainponorogo is enough to meet the information needs of students of the Faculty of Ushuluddin, Adab and Da'wah class of 2020 as an information media that requires more lecture information posts.

Public transport agencies use social media as an essential tool for communicating mobility incidents to passengers. However, while the short term, day-to-day information about transport phenomena is usually posted in social media with low latency, its availability is short term as the content is rarely made an aggregated form. Social media communication of transport phenomena usually lacks GIS annotations as most social media platforms do not allow attaching non-POI GPS coordinates to posts. As a result, the analysis of transport phenomena information is minimal. We collected three years of social media posts of a polish public transport company with user comments. Through exploration, we infer a six-class transport information typology. We successfully build an information type classifier for social media posts, detect stop names in posts, and relate them to GPS coordinates, obtaining a spatial understanding of long-term aggregated phenomena. We show that our approach enables citizen science and use it to analyze the impact of three years of infrastructure incidents on passenger mobility, and the sentiment and reaction scale towards each of the events. All these results are achieved for Polish, an under-resourced language when it comes to spatial language understanding, especially in social media contexts. To improve the situation, we released two of our annotated data sets: social media posts with incident type labels and matched stop names and social media comments with the annotated sentiment. We also opensource the experimental codebase.

Inequality is a critical issue that has been persistent throughout American history and remains a prevailing topic of discussion, concerning many Americans. The rise of social media has altered the way political conversations about inequality are held, as current politicians frequently utilize these platforms to communicate with voters to increase salience of particular issues. While previous studies have found that voter responses to political candidates’ social media posts may cause them to alter their issue campaigns during elections, this article investigates how senate candidates frame wealth, education, and housing inequality on social media and quantitates the impact on their election results. Using a sample of 14 politicians’ posts on the social media X from March 1, 2022 to November 8, 2022, and for senate races across 9 states representative of the widest range in inequalites, this study found that thematic framing was more commonly used in media posts. A logistic model was constructed which predicted electoral outcome with 78.6% accuracy and suggested that a strategic combination of episodic and thematic framing may enhance a candidate’s electoral success on social media platforms.

PA/LTC Goes Around the World in Online Communities

The use of public social media tools by federal, state, and local government agencies has evolved from novelty to commonplace. Citizens, comfortable using social media in their personal lives, expect to be able to interact with government officials in a similar manner. Government agencies, eager to be viewed as open and transparent, embrace the ease with which they can use social media to share information with the public. Public administrators and IT professionals at all levels of government use these technologies to deliver services, communicate information, respond to emergencies, and facilitate interactions between the government and the community. The Federal Government Social Media Wiki lists 123 government entities, and all but one employ at least one official public social media tool (GovSM, 2014). The one entity, the Occupational Safety and Health Administration (OSHA), does have a presence in social media, however, through the Department of Labor’s Twitter account. A 2012 study conducted by the National Association of State Chief Information Officers (representing state chief information officers and information technology executives and managers from U.S. state governments) revealed that 100% of respondents reported that their states use social media in some manner. A study conducted by the International City/County Management Association (ICMA) revealed that 84% of responding local governments maintain a social media presence (NASCIO, 2013, p. 1). The Federal Records Act (44 U.S.C. 3301) defines federal records as any material that is recorded, made, or received in the course of federal business, regardless of its form or characteristics, and is worthy of preservation (NARA, 2013). State and local governments employ similar definitions when identifying records for which they are responsible. Some social media content is likely to meet the definition of a record in use by the government entity and must be managed according to applicable laws, regulations and agency policies. “The backbone of a transparent and accountable government is good records management. To put it simply, the Government cannot be accountable if it does not preserve-and cannot find-its records” (NARA, 2014, 29). Those responsible for records management face numerous challenges, including identifying social media records, capturing records in a manner that ensures authenticity, disposing of records that no longer have value, and ensuring access by preserving records of value and making them available to the public.