Articles

Social media platforms like X (formerly Twitter) generate vast volumes of user-generated content that provide real-time insights into public sentiment. Despite the widespread use of traditional machine learning methods, their limitations in capturing contextual nuances in noisy social media text remain a challenge. This study leverages the Sentiment140 dataset, comprising 1.6 million labeled tweets, and develops predictive models for binary sentiment classification using Naive Bayes, Logistic Regression, and the transformer-based BERT model. Experiments were conducted on a balanced subset of 12,000 tweets after comprehensive NLP preprocessing. Evaluation using accuracy, F1-score, and confusion matrices revealed that BERT significantly outperforms traditional models, achieving an accuracy of 89.5% and an F1-score of 0.89 by effectively modeling contextual and semantic nuances. In contrast, Naive Bayes and Logistic Regression demonstrated reasonable but consistently lower performance. To support practical deployment, we introduce SentiFeel, an interactive tool enabling real-time sentiment analysis. While resource constraints limited the dataset size and training epochs, future work will explore full corpus utilization and the inclusion of neutral sentiment classes. These findings underscore the potential of transformer models for enhanced public opinion monitoring, marketing analytics, and policy forecasting.

The national museum of a country, as a cultural symbol of the nation, plays an important role in cultural communication at home and abroad. This study explores the online brand identity construction of two national museums—the British Museum and the National Museum of China—to inform cultural brands of the discursive strategies to distinguish themselves from others and communicate with their audiences effectively. Informed by multimodal critical discourse analysis, this paper analyzes the websites of the two museums and their social media posts, depicts their brand identity prisms, and evaluates the effectiveness of their online communication. The results show that both museums use multimodal and hypertextual resources to create unique and congruent brand images in website design and social media interaction with their target audiences, fulfilling the institutional functions of museums as the symbol of national culture or world civilization. They express differential personalities and cultural values to reinforce their brand identities in different sociocultural and political contexts. The findings may provide insight into the use of multimodality in online communication for cultural institutions to enhance their brand images and promote cultural exchanges.

Quantitatively, the study adopted a descriptive research design. The population of this study comprised two thousand (2000) students in the four (4) senior high schools (Edinaman Senior High, Eguafo Senior High, Peter Hold Book Senior High and Komenda Senior Technical Institute) in Komenda Edina Eguafo Abirem municipality. Purposive, simple random and stratified sampling techniques were used to select two hundred students from the four for this study. A questionnaire was the main instrument for data collection. There are more adverse effects of social media network participation on academic performance than positive effects. Social media network sites serve as a useful medium for enhancing students’ academic performance if properly used. Therefore, SHS students should be guided to use social media properly to enhance their academic performance. It is recommended that regular counselling by school authorities and parents for students who participate in social media networks should be done to prevent improper use of social media and avoid addiction and its consequences. It is also recommended that teachers should encourage students to use the right grammar and correct spelling of words when participating in social networks to help stop the negative effect it has on students’ academic performance. It is once again recommended that all stakeholders should be involved in educating students on the proper use of social media networks for their academic work as well as the dangers of improper use on their academic performance and social well-being.

Despite the pervasive nature of internet use among adolescents and young adults, there is not enough knowledge about whether and how involvement in social media influences substance use patterns and the risk of drug use-related problems. This study was conducted to examine the complex relationship between substance use-related social media engagement (viewing, liking, commenting, and posting the substance use-related social media content) and the drug use-related problem in adolescents from public perception. We surveyed to determine the perception of social media users regarding the association between substance use-related social media content and substance/drug abuse problems. An anonymous online questionnaire was conducted to collect the response from each participant. The response was generated after collecting the data from 126 users of mixed ages. The data was stringently analyzed, and the response was displayed in the form of bar charts. The primary findings indicated a significant relationship between drug/alcohol-related social media engagement and drug/alcohol-related problems. From public perception, a positive correlation was found between the engagement in the drug use-related content and drug use associated problems. However, further research is needed to determine the right direction of these associations that can provide substantiative solutions for numerous interventions aiming to prevent drug use-related adverse consequences.

With numerous unique physical, mental, psychological, and emotional challenges associated with being a university-level student-athlete, it can be assumed that student-athletes may be at great risk of mental health conditions such as burnout. Burnout results from the interaction of three different elements: physical or emotional exhaustion, sport devaluation, and reduced athletic accomplishment. This study sought to answer the following research questions: (1) <i>Why do student-athletes experience burnout in their sport</i>?, and (2) <i>What can be done to avoid burnout</i>? using standard qualitative interviewing techniques of a Division I Women’s Soccer coach. There were two prominent themes answering research question 1: <i>Perfection and Performative Social Media</i> and <i>It’s a Job and Coach is the Boss</i>. There were three prominent themes identified answering research question 2: <i>Parental Influence</i>, <i>De-Professionalize Amateur</i><i><b> </b></i><i>Sport</i>, and <i>Value </i><i>Athletes’</i><i> Time</i>. Where this work differs from other qualitative studies regarding athlete burnout, is that it explores the perceptions and opinions of a coach. The coach interviewed for this study clearly expressed concerns for his student-athletes and their holistic well-being. In addition to a continuation of scholarship through the student-athletes lens, more research conducted exploring the perspectives of coaches, parents, and institutional administrators in pursuit of solutions to mitigating the effect of burnout on student-athletes is of value.

A survey on food choices with a randomized sample population of individuals using various social media in Nigeria was conducted during the COVID1-19 pandemic. The data generated was subjected to basic standard statistical analysis. The parameters indicated that 94% of the population is young adults, 58.9 % percent are city dwellers, 63.6% are students, 23.4 % are into business, 86.9% are graduates; 73.8% consume various diets, 23.4% are vegetarians and only 2.8% fed only on proteins, 30.8% of them go on two meals per day. The most choices on influence on food purchases decision are hunger (26.2%), mood (26.2%), past experience (45.8%), quality of the food products (66.7%), cost of the food products (50.5%) and government approval (28%). Also,other most preferred choices are for self-prepared food (40.21%), enhanced local diets (36 %), and a blend of foreign and local diets purchases (24%). Other highest choices include: easy preparation (37.4%), shelf life (29%); cute packaging (23.4%), swelling property preference (20.6%), minimal cooking time and energy preference (37.4%). The weighted sum, index and rank on factors influencing food choices showed that the influence of quality of food product ranked highest, followed by influence on cost. Also preference for enhanced local healthy diets to foreign ranked highest, minimal cooking time and energy costs ranked highest. These nutritional adaptations have implications to individuals, food scientists, manufacturers in the food industry, food regulatory agencies, government and other decision bodies.

Online shopping is a growing phenomenon and social media namely Facebook has radically changed consumers online purchase behaviour; especially the interactive information system of consumers, peers, and vendors. Similar to other online purchasing products or services, e-cigarette marketing in Facebook has potential. This study aims to determine the association between individual’s online interaction and e-cigarette purchase intention from Facebook vape groups. A cross-sectional study was conducted among 214 respondents using the Facebook platform from September to December 2019. Data were collected via a self-administered questionnaire. The Chi-square test was used for data analyses using SPSS (version 25.0). Most of the participants were male; the mean age of the respondents was 27.41 ± 2.1. Total 93.9% (201 of 214) and 56.1% (120 of 214) respondents were vaper and smoker respectively. Among the non-smokers, most of the respondents were vaper (84 of 94, 89.4%). Consumers smoking and vaping status were associated with each other (χ2 = 6.11, P=0.01). There was an association between vaping status and purchase intention of e-cigarettes from the Facebook vape group (χ2 = 5.06, P=0.02). Online interactions, namely like (χ2 = 5.88, P <0.01), post (χ2 = 7.16, P <0.01) and sharing (χ2 = 10.14, P <0.01) of the e-cigarette related information or advertisements in social media were associated with purchase intention of e-cigarettes from Facebook vape group. This study revealed individuals vaping and online interactions were associated with an online purchase the intention of e-cigarette in Facebook. Public health researchers and policymakers might contemplate the regulatory environment of online marketing of e-cigarettes to curtail the uptake of e-cigarettes among non-smokers.

The field of sentiment analysis is a crucial aspect of natural language processing (NPL) and is essential in discovering the emotional undertones within the text data and, hence, capturing public sentiments over a variety of issues. In this regard, this study suggests a deep learning technique for sentiment categorization on a Twitter dataset that is based on Long Short-Term Memory (LSTM) networks. Preprocessing is done comprehensively, feature extraction is done through a bag of words method, and 80-20 data is split using training and testing. The experimental findings demonstrate that the LSTM model outperforms the conventional models, such as SVM and Naïve Bayes, with an F1-score of 99.46%, accuracy of 99.13%, precision of 99.45%, and recall of 99.25%. Additionally, AUC-ROC and PR curves validate the model’s effectiveness. Although, it performs well the model consumes heavy computational resources and longer training time. In summary, the results show that deep learning performs well in sentiment analysis and can be used to social media monitoring, customer feedback evaluation, market sentiment analysis, etc.