Influencer Identification System Design Using Machine Learning Techniques

Navigating Social Media in #Ophthalmology

Use of different social media platforms has increased radically over the past decade, emerging as an important part of adolescents and young people's everyday life. This might exert potential adverse effects on sleep quality and daytime performance of young adults. To assess the relation between use of social media platforms and sleep quality among public secondary school students. A cross-sectional study was conducted on 961 students in Aseer region, Saudi Arabia. Students were asked to fill in a structured interview questionnaire covering personal data, pattern of social media use, sleep quality using The Pittsburgh Sleep Quality Index (PSQI) and their mental health status using the depression, anxiety and stress scale (DASS-21). Students' ages ranged from 15 to 20 years with a mean age of 16.7 ± 2.1 years old. A total of 570 (59.3%) students were females. Tiktok (80%), Snapchat (77.9%), Instagram (63.8%) and YouTube (58.8%) were the most reported platforms used. Regarding their sleep quality, 34.7% of students were poor sleepers. TikTok use (OR 1.33, 95% CI 1.01-1.77), hours spent on social media (OR 1.26, 95% CI 1.16-1.37) and having moderate to severe depressive symptoms (OR 1.69, 95% CI 1.19-2.40) were significant independent predictors of poor sleep among the studied sample. The present study emphasized the association between prolonged use of social media and poor sleep quality among Saudi adolescents. Awareness and behavioral change strategies and activities concerning the drawbacks of poor sleep and proper use of social media are urgently called for to control mental and physical health consequences of poor sleep and social media addiction.

BACKGROUND:Social media platforms are progressively developing as a rich source of mass communication. Increasing mental health awareness with the help of social media can be a good initiative to reach out to a large number of people in a short time frame. This study was conducted to understand the usefulness of social media platforms for health promotion.MATERIALS AND METHODS:It was a qualitative study to evaluate the effectiveness of social media platforms in hosting health promotion campaigns in the field of mental health, which was observed over 5 months from May to September 2019 to reach more people for effective information dissemination. The campaigns were as follows (1) The Buddies for Suicide Prevention: an online campaign to create awareness about suicide prevention. The campaign included script writing, slogan writing, poster making, and short films making, organized for the general public who were interested to take part; (2) The #Iquitobacco was a 21-day campaign with an idea of tobacco cessation in the community, conducted among social media viewers who were willing to participate; and (3) #Migrainethepainfultruth was yet another campaign conducted among the social media viewers who were interested to participate. All the campaigns were conducted using two famous social media platforms commonly used by young adults. Descriptive statistics such as frequency and proportions were computed for the number of likes and shares.RESULTS:The Facebook and Instagram posts concerning all the campaigns brought about a considerable amount of reach to the targeted population. After the campaigns, the page reached to around 10.3 k people (both fans and nonfans).CONCLUSIONS:Use of social media to conduct mental health campaigns is an effective initiative as one can reach out to several people over a short time period. There is an increasing trend in the awareness of mental health with the effective use of digital media as a platform for disseminating information.

The recent Covid 19 pandemic revealed the global challenge posed by infectious diseases. Vaccines are a crucial tool in preventing pandemics, as evidenced by their success in controlling past outbreaks. The rise of information and communication technology has introduced social media platforms as potential game-changers in both preventing and managing future pandemics. However, these same platforms can also be a double-edged sword, hindering the uptake of essential vaccination services. This study investigated the association between social media use and vaccine hesitancy among medical students. The study was designed as an institution based cross sectional study of 423 medical students in Kenya Medical Training College and University of Kabianga in Kericho County. Stratified sampling was used to decide on the two institutions and systematic random sampling was used to select the study participants. Research administered questionnaires were used to collect data on the socio-demographic characteristics, use of social media platforms, social media campaigns, and uptake of Covid 19 vaccines. The collected data was analyzed using Statistical Package for Social Sciences version 25. Chi square was used to establish the association between the independent variables and uptake of Covid 19 vaccines. The variables that were significantly associated with hesitancy to Covid 19 vaccines were further analyzed using binary logistic regression. The confidence interval (CI) was set at 95% and statistical significance was considered at p < 0.05. The study found significant associations between vaccine hesitancy and several factors, including academic level, preferred social media platform, the influence of social media on attitudes towards vaccines, concerns about vaccine safety and efficacy, and confidence in vaccines. The findings present social media as a potential platform for promotion of vaccines utilization during pandemics when used well.

Aim: This study aimed to assess dental students' social media (SM) usage and their perceptions of and attitudes towards e-professionalism. Materials and methods: This study used a paper-based questionnaire administered to undergraduate dental students (4th year and interns) at the University of Benghazi, Libya, in 2022. The questionnaire included closed-ended questions to recognize dental students' use of social media platforms, their privacy settings and their perceptions and attitudes towards e-professionalism. The responses were compared according to the study year and whether the participants received professionalism-related training. The chi-square test was used for all comparisons, with the significance level set at p˂0.05. Results: A total of 364 students were included in the analysis (response rate: 73.5%). Almost all participants used multiple SM platforms. However, the most frequently used platforms were Facebook (84.3%) and Telegram (76.9%). More than half of the respondents (57.5%) considered their online behaviour to be a personal activity that would not affect their job opportunities in the future (71.1%). On the other hand, a considerable proportion of the respondents described posting information about dental patients as unprofessional (70.9%). Overall, a small proportion of participants (6.4%) considered communication with patients on SM unprofessional. Interns, however, were more likely to report this as unprofessional (P = 0.026). Conclusion: The current study demonstrated the widespread popularity of SM platforms, notably Facebook and Telegram, among dental students at the University of Benghazi. The study also highlights concerns about students’ perceptions of what constitutes unprofessional behaviours when using SM platforms with blurred personal-professional boundaries. The study's findings underscore the necessity of creating guidelines for social media use among Libyan dental students and incorporating e-professionalism into the dental curriculum.

The increased use of social media in Mexico has given rise to the "fear of missing out" (FoMO) phenomenon, especially among adolescents. This study aimed to measure the extent of FoMO among junior high school students in the metropolitan area of Guadalajara, Mexico, during the COVID-19 pandemic. Additionally, this study explored the association between FoMO levels and demographic characteristics, as well as the type and frequency of social media use. A cross-sectional survey was conducted from November 2021 to January 2022 in four junior high schools. A total of 1264 students (656 females and 608 males) aged 11-16 years completed the Fear of Missing Out Scale, adapted to the Mexican context. Data on demographics, social media usage, and school shifts were collected. Statistical analyses were performed using t-tests, ANOVA, and correlation coefficients. The mean FoMO score was 1.79 ± 0.64, with higher scores observed in females (p < 0.001) and students attending morning shifts (p = 0.001). Significant associations were found between higher FoMO scores and the use of social media platforms like Instagram, TikTok, and Pinterest (p < 0.001 for each). The most frequently used social media platforms were WhatsApp (1093), TikTok (828), and Instagram (583). Participants who used social media all week exhibited significantly higher FoMO scores than those who used it only on weekends (p < 0.001). FoMO is a significant phenomenon among junior high school students in Guadalajara, Mexico, particularly among females and those who use multiple social media platforms. The findings suggest a need for interventions to manage social media use and mitigate FoMO-related negative health outcomes in this population.

In South Africa, social media usage has consistently increased over time, with young individuals being the most active users. However, there are concerns about mental illness, such as depression, as a result of the surge in social comparison. This study explored the relationship between social media usage and mental health among young adults in the Buffalo City Metropolitan Municipality. This study used a quantitative research approach and was based on the positivism paradigm. Data was collected from 127 young individuals aged 14 to 35 who live in the Buffalo City Metropolitan Municipality through the use of structured questionnaires. The data collected was analysed using a descriptive statistical package for the social sciences. The findings of the study amongst others showed that the young adults spend an average of 6 hours per day on social media platforms. Also, the fear of missing out (FoMO) was identified as another major reason why young adults stay on social media platforms for long hours every day. Based on the results presented in this study, one can convincingly state that the excessive use of social media is negatively contributing to the mental health status of young adults. Some of these detrimental impacts include depression, anxiety, low self-esteem, suicide and other mental health issues. The study recommends amongst others that an urgent and continuous well-structured awareness campaign be made to help sensitise the young adults on the danger of excessive use of social media platforms, both on their mental health status and life in general.

Spatial Patterns of Purposeful Social Networking and Socioeconomic Influences: Towards a Mature, Inclusive Networked Society in the U.S.

Social commerce was established with the growing commercial use of social media platforms, centered around e-commerce features and actors (buyers, influencers, and sellers) which provide user-generated content through recommendations on products and services. Important factors are both the utilization of social media platforms as trusted sources by users and the trusted content from users posting their experiences and opinions. This study focuses on Swiss consumers (9 out of 10 Swiss residents are active online) and their usage of social media, e-commerce, and social commerce as a source of trusted product information and platforms to share their own product experiences. While social media usage in Switzerland is high (almost all online users are using some form of social media), only one-third are using social media (primarily YouTube) as a source of information that guides decision-making. Merely one in ten respondents post their experiences—satisfaction or recommendations for products and services—on social media at least once a month. Our research data show that in Switzerland, social commerce is an underdeveloped marketing concept as to available e-commerce features and the degree of trusted user-generated content about products and services on social media platforms.

Current Social Media Use Among Radiation Oncology Trainees

Advancement in information and communication technologies has led to the emergence of Social Media (SM). SM platforms are used to facilitate information sharing and learning. Literature shows that SM platforms have been associated with effective learning and improved student academic performance. Despite the recorded successes, the use of SM platforms to support students’ learning in built environment programmes has not been fully investigated. To address this knowledge gap, the current study examines the barriers and drivers encouraging the use of SM technologies to support learning and teaching in built environment programmes based on the perspective of university students. The data for the study were collected using semi-structured interviews and questionnaires. The mean score (MS) was used to analyse the quantitative data, while the qualitative data were analysed using thematic analysis. The top-two drivers for using SM technologies are the need for collaboration among students and compatibility with a twenty-first-century education. The top-two barriers to using SM platforms are the cost of internet subscriptions and the quality of internet services available in a particular location. The result shows that students are willing to incorporate elements of online learning. The research contributes to the current body of knowledge by highlighting the drivers and barriers to using SM to support learning. Moreover, the outcome of this study may guide administrators in higher institutions and other education policymakers, specifically for developing countries, to make informed decisions regarding integrating SM technologies into learning and teaching.

This chapter examines the phenomenon of internet users attempting to report and prevent online child sexual exploitation (CSE) and child sexual abuse material (CSAM) in the absence of adequate intervention by internet service providers, social media platforms, and government. The chapter discusses the history of online CSE, focusing on regulatory stances over time in which online risks to children have been cast as natural and inevitable by the hegemony of a “cyberlibertarian” ideology. We illustrate the success of this ideology, as well as its profound contradictions and ethical failures, by presenting key examples in which internet users have taken decisive action to prevent online CSE and promote the removal of CSAM. Rejecting simplistic characterizations of “vigilante justice,” we argue instead that the fact that often young internet users report feeling forced to act against online CSE and CSAM undercuts libertarian claims that internet regulation is impossible, unworkable, and unwanted. Recent shifts toward a more progressive ethos of online harm minimization are promising; however, this ethos risks offering a new legitimizing ideology for online business models that will continue to put children at risk of abuse and exploitation. In conclusion, we suggest ways forward toward an internet built in the interests of children, rather than profit.

Nowadays, with the increasing number and use of social media platforms, people now share their experiences about a product they have bought or a place they have been to on social media platforms more frequently. Considering the volume of data on social media platforms, it is considered that there is some meaningful information for institutions or companies in the reviews and experiences shared on social media platforms. As such, it is important to improve the methods of extracting meaningful information from the reviews and experiences shared on social media and to know which method is better. In this study, the classification successes of the bag of words and the fastText word representation methods, which are among the word representation methods in sentiment analysis methods mentioned above, were compared by using Turkish reviews performed for touristic places. Besides, while performing the comparison process, it was measured whether the process of separating the words into their roots and negation of the words, which is the preliminary stage of the sentiment analysis process, contributed to the classification success. In the study, both two-class (positive, negative) sentiment analysis and three-class (positive, negative, neutral) sentiment analysis were performed. Six data sets were created to carry out the mentioned comparison operations. The data sets were first classified using the Naive Bayes (NB), Multinomial Naive Bayes (MNB), k-Nearest Neighbor (k-NN) and Support Vector Machines (SVM) algorithms, which are frequently used in text mining, and based on bag of words word representation method, they were classified with WEKA program. After the test results of all data sets were obtained according to the bag of words word representation method, the tests of the fastText word representation method were carried out using the fastText library of the Python programming language. Classification procedures were carried out with 10-fold cross-validation methods, and f-score values of the classification processes were obtained. Finally, it was determined that bag of words word representation method performed a more successful classification than the fastText word representation method in two-class emotion analysis, while the fastText word representation method performed a more successful classification process than bag of words word representation method in three-class emotional analysis. It was observed that the process of separating the words into their roots and negating the words, which are the preliminary processes of sentiment analysis, did not contribute positively or negatively to the classification processes performed with the fastText word representation method. However, it was determined that it had a minor contribution to sentiment analysis processes performed by using bag of words word representation method. In the two-class sentiment analysis, the most successful classification result was achieved by using the machine learning model created with the SVM algorithm with the value of 0.91 f-score employing bag of words word representation method. In the three-class sentiment analysis, the most successful classification result was achieved with the machine learning model created using the fastText word representation method with the value of 0.78 f-score.

With the advent of technological advancements and the widespread Internet connectivity during the last couple of decades, social media platforms (such as Facebook, Twitter, and Instagram) have consumed a large proportion of time in our daily lives. People tend to stay alive on their social media with recent updates, as it has become the primary source of interaction within social circles. Although social media platforms offer several remarkable features but are simultaneously prone to various critical vulnerabilities. Recent studies have revealed a strong correlation between the usage of social media and associated mental health issues consequently leading to depression, anxiety, suicide commitment, and mental disorder, particularly in the young adults who have excessively spent time on social media which necessitates a thorough psychological analysis of all these platforms. This study aims to exploit machine learning techniques for the classification of psychotic issues based on Facebook status updates. In this paper, we start with depression detection in the first instance and then expand on analyzing six other psychotic issues (e.g., depression, anxiety, psychopathic deviate, hypochondria, unrealistic, and hypomania) commonly found in adults due to extreme use of social media networks. To classify the psychotic issues with the user's mental state, we have employed different Machine Learning (ML) classifiers i.e., Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes (NB), and K-Nearest Neighbor (KNN). The used ML models are trained and tested by using different combinations of features selection techniques. To observe the most suitable classifiers for psychotic issue classification, a cost-benefit function (sometimes termed as ‘Suitability’) has been used which combines the accuracy of the model with its execution time. The experimental evidence argues that RF outperforms its competitor classifiers with the unigram feature set.

This research has evaluated the effectiveness of the use of social media for the promotion of public health. Social media platforms have been used to promote the flu vaccine among students and employees on Saint Martin’s University’s campus. Saint Martin’s University’s e-mail and twitter page have been utilized as the primary means to send messages consist of images and texts that urge SMU community members (students and employees) to take the flu shot to protect themselves and others around them. Moreover, examination and evaluation of the existing literature and some academic studies that were conducted previously to assess the efficacy of the utilization of social media for promoting public health has been done. The participants in this research were students and employees attending SMU during the Fall semester of 2017. It was hypothesized that the number of students and employees who got the flu vaccine throughout the Fall semester of 2017 will surpass the number of students and employees received the flu shot in past years where the social media platforms were not employed for the promotion of the flu shot on SMU campus.