Use Of Twitter Research Articles

Associations between social networks, messaging apps, addictive behaviors, and sleep problems in adolescents: the EHDLA study

ObjectiveThe current study aims to provide a comprehensive analysis of the relationships between social network (SN) use, messaging apps use, and addictive behaviors related to SNs, and sleep-related problems in a sample of Spanish adolescents.MethodsThis was a cross-sectional study using data from the Eating Healthy and Daily Life Activities (EHDLA) project, which involved adolescents aged 12–17 years from three secondary schools in Valle de Ricote (Region of Murcia, Spain). A sample of 632 adolescents was studied. The use of SN (i.e., Facebook, Twitter, Instagram, Snapchat or TikTok) or messaging applications (i.e., WhatsApp) was assessed via a scale including one item for each SN, in which adolescents were asked what type of SN they used and the usage profile of each SN. The Short Social Networks Addiction Scale-6 Symptoms (SNAddS-6S) was used to determine SN addictive behaviors. Generalized linear regression analyses with a negative binomial distribution were performed to determine the associations of SN use or SN addictive behaviors with sleep-related problems. These analyses were adjusted for age, sex, body mass index, socioeconomic level, physical activity, sedentary behavior, and adherence to the Mediterranean diet.ResultsHigher SN use was related to greater presence of sleep-related problems [prevalence ratio (PR) = 1.04; 95% confidence interval (CI) 1.01–1.07; p = 0.015]. Additionally, the higher the score on the addictive behaviors toward SN use scale was, the more sleep-related problems were identified (PR = 1.15; 95% Cl 1.09 to 1.21; p < 0.001). Specifically, only the use of Twitter was significantly associated with sleep-related problems (PR = 1.10; 95% Cl 1.01 to 1.21; p = 0.035). In terms of addictive behaviors related to SN use, mood modification, relapse, withdrawal, and conflict were significantly associated with sleep-related problems (mood modification: PR = 1.58; 95% CI 1.36 to 1.84; p < 0.001; relapse: PR = 1.24; 95% CI 1.07 to 1.43; p = 0.004; withdrawal: PR = 1.28; 95% CI 1.08 to 1.51; p = 0.004; conflict: PR = 1.19; 95% CI 1.01 to 1.39; p = 0.037).ConclusionOur results suggest a relationship between SN use, SN addictive behaviors, and sleep-related problems in adolescents. These cross-sectional results should be confirmed in longitudinal and intervention studies.

Understanding organisation public relations through Twitter communication for the European super league

ABSTRACT Research question Twitter (X) is often praised as a means for mutual beneficial relationships and dialogue to be built between a sport organisation and its fans, thus encouraging the implementation of Organisational Public Relations (OPR). We examine this proposition by focusing on the use of Twitter by football clubs and their fans to explore the role and nature of OPR and how this evolves when key business decisions are communicated via social media and when fans actively react to such strategic communication. Research methods Content analysis was conducted in six UK football clubs’ tweets when joining and then withdrawing from the European Super League, and in fans’ responses to them, in order to identify how OPR manifests on social media. Results and Findings The findings reveal that fans were displeased with the way in which clubs communicated their decisions while requesting a dialogue with the clubs which is currently missing, and demanding a substantial, respectful and beneficial relationship to be built with them. Implications By focusing on both sides of OPR, the clubs and the fans, in our study, we uncover that OPR can take different forms and shapes when Twitter is used, depending on the directions of the communication and the relationships built. As such, we identify and propose the 4I framework, which takes into account the different forms of relationships between parties and the direction of communication adopted among them, capturing thus the four types of OPR domains, across which organisations and publics ebb and flow.

US State Public Health Agencies' Use of Twitter From 2012 to 2022: Observational Study.

Twitter (subsequently rebranded as X) is acknowledged by US health agencies, including the US Centers for Disease Control and Prevention (CDC), as an important public health communication tool. However, there is a lack of data describing its use by state health agencies over time. This knowledge is important amid a changing social media landscape in the wake of the COVID-19 pandemic. The study aimed to describe US state health agencies' use of Twitter from 2012 through 2022. Furthermore, we organized our data collection and analysis around the theoretical framework of the networked public to contribute to the broader literature on health communication beyond a single platform. We used Twitter application programming interface data as indicators of state health agencies' engagement with the 4 key qualities of communication in a networked public: scalability, persistence, replicability, and searchability. To assess scalability, we calculated tweet volume and audience engagement metrics per tweet. To assess persistence, we calculated the portion of tweets that were manual retweets or included an account mention. To assess replicability, we calculated the portion of tweets that were retweets or quote tweets. To assess searchability, we calculated the portion of tweets using at least 1 hashtag. We observed a COVID-19 pandemic-era shift in state health agency engagement with scalability. The overall volume of tweets increased suddenly from less than 50,000 tweets in 2019 to over 94,000 in 2020, resulting in an average of 5.3 per day. Though mean tweets per day fell in 2021 and 2022, this COVID-19 pandemic-era low was still higher than the pre-COVID-19 pandemic peak. We also observed a more fragmented approach to searchability aligning with the start of the COVID-19 pandemic. More state-specific hashtags were among the top 10 during the COVID-19 pandemic, compared with more general hashtags related to disease outbreaks and natural disasters in years before. We did not observe such a clear COVID-19 pandemic-era shift in engagement with replicability. The portion of tweets mentioning a CDC account gradually rose and fell around a peak of 7.0% in 2018. Similarly, the rate of retweets of a CDC account rose and fell gradually around a peak of 5.4% in 2018. We did not observe a clear COVID-19 pandemic-era shift in persistence. The portion of tweets mentioning any account reached a maximum of 21% in 2013. It oscillated for much of the study period before dropping off in 2021 and reaching a minimum of 10% in 2022. Before 2018, the top 10 mentioned accounts included at least 2 non-CDC or corporate accounts. From 2018 onward, state agencies were much more prominent. Overall, we observed a more fragmented approach to state health agency communication on Twitter during the pandemic, prioritizing volume over searchability, formally replicating existing messages, and leaving traces of interactions with other accounts.

Farmers Markets Marketing Strategies in the Digital Era in the USA

The COVID-19 pandemic significantly disrupted agribusiness operations nationwide. This study analyzed text data from the websites of 200 farmers markets across the United States using a “Text Mining Analytics” approach. We created word clouds to examine three key aspects of farmers markets: (i) digital marketing strategies adopted in response to the pandemic, (ii) popular products sold, and (iii) market operating days and times. Our findings revealed a notable increase in online presence and identify effective digital promotional strategies, such as the use of Facebook, websites, Instagram, Twitter (now X), and blogs. Additionally, we highlighted the most popular products available at farmers markets, including tomatoes, baked goods, peppers, apples, plants, and lettuce. Furthermore, we found that Wednesdays, Thursdays, Saturdays, and Sundays are favored operating days. This research offers valuable insights for policymakers, market managers, and vendors, aiding them in making informed decisions.

Collaborative authoritarianism and its unintended consequences

ABSTRACT Why do authoritarian regimes maintain access to open U.S.-owned social media platforms like Twitter and how do pro-government supporters use them? While the literature on consultative authoritarianism explains how limited public engagement through purpose-built input institutions can be used to gauge public grievances and boost regime legitimacy, we know less about the implications of open social media applications and why the regime maintains access to them despite their subversive potential. This article argues that open platforms allow pro-government supporters to perform public opinion and police views that do not align with official state talking points, creating an impression of a consensus about what society “thinks.” Yet, they might push the government to respond to their demands that might not align with official state interests. I label this practice of enlisting supporters and segments of society for political control collaborative authoritarianism. This practice extends to purpose-built law enforcement apps, engaging broader segments of the population. Introducing the case of Twitter use in Saudi Arabia, this article draws on around 100 interviews that I conducted with patriotic and nationalist journalists, intellectuals, and Twitter influencers across Saudi Arabia between November 2021 and May 2022. The article provides novel insights into the grassroots politics of digital authoritarianism as well as the mobilization of illiberal movements beyond Saudi Arabia.

Use of Digital Tools in Arbovirus Surveillance: Scoping Review.

The development of technology and information systems has led to important changes in public health surveillance. This scoping review aimed to assess the available evidence and gather information about the use of digital tools for arbovirus (dengue virus [DENV], zika virus [ZIKV], and chikungunya virus [CHIKV]) surveillance. The databases used were MEDLINE, SCIELO, LILACS, SCOPUS, Web of Science, and EMBASE. The inclusion criterion was defined as studies that described the use of digital tools in arbovirus surveillance. The exclusion criteria were defined as follows: letters, editorials, reviews, case reports, series of cases, descriptive epidemiological studies, laboratory and vaccine studies, economic evaluation studies, and studies that did not clearly describe the use of digital tools in surveillance. Results were evaluated in the following steps: monitoring of outbreaks or epidemics, tracking of cases, identification of rumors, decision-making by health agencies, communication (cases and bulletins), and dissemination of information to society). Of the 2227 studies retrieved based on screening by title, abstract, and full-text reading, 68 (3%) studies were included. The most frequent digital tools used in arbovirus surveillance were apps (n=24, 35%) and Twitter, currently called X (n=22, 32%). These were mostly used to support the traditional surveillance system, strengthening aspects such as information timeliness, acceptability, flexibility, monitoring of outbreaks or epidemics, detection and tracking of cases, and simplicity. The use of apps to disseminate information to society (P=.02), communicate (cases and bulletins; P=.01), and simplicity (P=.03) and the use of Twitter to identify rumors (P=.008) were statistically relevant in evaluating scores. This scoping review had some limitations related to the choice of DENV, ZIKV, and CHIKV as arboviruses, due to their clinical and epidemiological importance. In the contemporary scenario, it is no longer possible to ignore the use of web data or social media as a complementary strategy to health surveillance. However, it is important that efforts be combined to develop new methods that can ensure the quality of information and the adoption of systematic measures to maintain the integrity and reliability of digital tools' data, considering ethical aspects.

Factors Influencing Community’s Acceptance of Twitter (X) on Improving Information Access in Tanzania’s Police Force

This study was conducted to investigate the acceptance of Twitter (X) for improving information access in Tanzania’s Police Force. The specific objectives of the study were to assess the community’s perceived usefulness of Twitter (X) in improving information access and to examine the community’s perceived ease of use of Twitter (X) for enhancing information access in Tanzania. The Technology Acceptance Model (TAM) guided this research. The study employed a cross-sectional research design using a quantitative research approach, while a stratified sampling technique was utilized to select 154 respondents. The population comprised 250 Tanzania Police officials, from which a sample size of 154 respondents was determined using Yamane’s formula. Out of the 154 questionnaires issued, 100 were returned, resulting in a response rate of 64 percent. Data were collected through a questionnaire and analysed using descriptive analysis and inferential analysis through multiple linear regression. The study findings indicated that the community’s perceived usefulness and perceived ease of use of Twitter (X) play significant roles in improving information access in Tanzania. The findings enhance the contribution of the Technology Acceptance Model (TAM) by unveiling the importance of its major constructs—perceived usefulness and perceived ease of use—in influencing information access within the police community. The research concluded that the Tanzania Police Force’s access to Twitter (X) is significantly influenced by perceived ease of use. Law enforcement officials use the platform more frequently as it becomes easier to navigate and more intuitive. Therefore, this study recommends that digital platforms should be utilized as long as they are user-friendly and provide value to individuals.

The use of TikTok by the police

Police agencies continue to use social media platforms as part of their operations. Although previous research has explored the police's use of Twitter (now referred to as X), Facebook, and other platforms, no known research has explored the police's use of TikTok. As part of the present research, we conducted a content analysis of all TikTok videos posted by the Vancouver Police Department (VPD) between January 2022 and June 2023 ( N = 96 videos). Our findings reveal that the VPD focused more on community-oriented content than law enforcement-oriented content in their videos. Our findings also reveal that many videos emphasized a networking strategy. Our research provides an empirical snapshot of how one police agency with a particularly popular TikTok account uses the platform. We highlight the relevance of our findings for research regarding policing and social media as well as policing practice.

Updated 5-Year Institutional Bibliometric Profiles for United States Neurosurgery Residency Programs and the Relationship Between Social Media Presence and Objective Departmental Metrics.

The authors report current 3-year and 5-year institutional bibliometric profiles and investigate the correlations between objective metrics of neurosurgical residency programs and social media presence, including residency program size, faculty count, Doximity rankings, and measures of research output. A list of neurosurgery residency programs was obtained through the Doximity Residency Navigator. Publication history of faculty members was compiled using Scopus and analyzed to create institutional bibliometric profiles from 2018-2022 to 2020-2022. Mann-Whitney U tests were used to compare departmental metrics for institutions with and without social media accounts. Spearman rank correlations were used to examine the relationship between social media following and metrics, and between Twitter following and methods of Twitter use. 74% (n = 86) of neurosurgery programs have a Twitter account, 47% (n = 55) have a Facebook account, 63% (n = 73) have Instagram accounts, and 16% (n = 19) have LinkedIn accounts. The most notable differences were found when comparing departments with and without Twitter accounts, where a difference was found in all metrics except the average H-index. Residency program size, faculty count, average H-index, 3-year and 5-year publication and citation counts per faculty, and institutional H-indices were significantly correlated with Twitter following. Higher Doximity rankings were correlated with Twitter following and Facebook likes. There is a greater increase in 5-year citations per publication from 2009-2013 to 2018-2022 for institutions that created departmental Twitter accounts after 2013. Articles that were tweeted about had higher 3-year citations per publication than the institution's overall 3-year citations per publication. Our findings provide updated insight into the relationship between social media presence and objective academic metrics of neurosurgery departments. We identify and quantify correlations between social media platforms and program characteristics, with a focus on research output. These metrics can be used to guide programs in their development of social media.

Small-grid urban flood prediction model using Twitter data and population GPS data - an example of the 2019 Nagano city flood

In this study, a small-grid urban flood prediction model integrating Twitter data and population GPS data was constructed using the 2019 Nagano City flood as an example, and the validity of these two data for the model was determined. Using natural language processing techniques, Twitter data was filtered to extract real-time information relevant to flooding. At the same time, geographic information processing techniques were applied to analyze the population GPS data and obtain the distribution of the local population. Based on these two types of data, we combined with terrain, land use, traffic and infrastructure data related to flooding, a real-time flood prediction model was constructed using the random forest algorithm with a basic unit of a 70 m × 70 m grid. An analysis of the model accuracy showed that, the model that included both GPS and Twitter data showed an improvement in prediction accuracy of about 8% compared to flood prediction models that do not have these data sources. This indicated that the integrated use of Twitter and GPS data allowed us for a more accurate representation of the dynamic characteristics of flood disasters, thereby improving the performance of real-time flood prediction models and increasing real-time awareness of flood events. This approach provided effective flood monitoring methods for disaster management authorities.

The Relationship Between Social Media Addiction and Perceived Stress in Adolescents.

The study was conducted to determine the relationship between social media addiction and perceived stress in adolescents. The study was conducted in a descriptive and cross-sectional design between September and December 2022 in secondary education institutions of the Provincial Directorate of National Education in a city center in eastern Turkey. The sample of the study consisted of a total of 716 adolescents who were studying in the ninth grade (145), 10th grade (198), 11th grade (216), and 12th grade (157) who met the inclusion criteria of the study at the time the study was conducted. The sample comprised individuals with diverse sociodemographic characteristics, including ages, genders, school success levels, parents' education levels, parents' job status, socioeconomic status, time spent on daily social media, and purposes of social media use of the adolescents. The "Sociodemographic Characteristics Form," "Social Media Addiction Scale for Adolescents (SMASA)," and "Perceived Stress Scale (PSS)" were used as the data collection tools. Ethical principles were fulfilled in the study. It was found that the average age of the adolescents who participated in the study was 15.71 ± 1.22, 58.1% were females, 41.1% had good school success, 90.5% had a mobile phone, 90.2% used WhatsApp, 56.8% said that their daily social media use time was between 1 and 3 h, and 64% said that their purpose of using social media was for entertainment and leisure. The mean SMASA score was 18.49 ± 6.98, and the mean PSS score was 42.11 ± 7.54. It was found in the study that the mother's employment status, phone ownership status, use of Instagram, Facebook, Twitter, WhatsApp, Snapchat, YouTube, TikTok, and LinkedIn accounts, daily social media use, time and purposes of using social media affected the mean SMASA score. Age, gender, school success, use of Instagram and Snapchat accounts, daily social media use time, and purposes of using social media affected the mean PSS score (p < 0.05). As a result of the study, a positive and low-level significant relationship was detected between social media addiction and perceived stress levels (p < 0.01). As the levels of social media addiction increase in adolescents, the perceived stress levels also increase. It was also found that some variables affected the social media addiction and perceived stress levels of adolescents.

Tweeter‐in‐chief: Dynamics of Trump's populist campaign against the Fed

AbstractSocial media is transforming how politicians communicate with the public, empowering elected officials to immediately reach target audiences. Scholars of the U.S. presidency in particular credit former President Donald Trump with revolutionizing the White House bully pulpit through his use of Twitter. Trump's bullying of the Federal Reserve and Fed Chair Jerome Powell for ever lower interest rates stands out amidst his often norm‐defying social media campaigns. Such attacks broke from recent practice: Trump's immediate predecessors largely refrained from telling the central bank what to do. What drove Trump's pressure campaign against the Fed? In this note, we identify and tally Trump's attacks, explore dynamics shaping his appeals, and demonstrate that financial headwinds—more so than economic or political barometers—reliably incited Trump to pressure the Fed.

Presidential Activism on Social Media: Multidimensional Analysis and Empirical Examination of Presidential Twitter Use in Europe

Since the advent of mass media, ‘going public’ has been a key tool in the strategic inventory of presidents seeking to promote their policies to politicians and the public. Over the last decade, social media has offered presidents and their office with a new platform to address the nation directly without relying on traditional media gatekeepers. Nevertheless, both ‘going public’ strategies and presidents’ use of social media have almost exclusively been researched in the context of the presidential systems. The aim of this article is to extend research and offer the first systematic study of presidential Twitter use in European semi-presidential systems. We conceptualise presidential Twitter use as a form of presidential activism that is complementary to the use of formal powers or informal attempts to influence policy. Whereas the latter are driven by institutional or partisan conflict, going public strategies and presidential Twitter use primarily address societal concerns and, hence, are motivated by contextual factors outside the core realm of party politics. Instead, we should expect social conflict and societal grievances to determine demand and supply of presidential Twitter use. We test our propositions using a new dataset of tweets by presidents in European semi-presidential systems 2010–2020.

Do political elite endorsements influence online mobilization? A study of Twitter behavior in Narendra Modi’s 2019 election campaigns

ABSTRACT Modern campaigns increasingly rely on social media to influence voters, with Twitter offering affordances that enable direct communication between politicians and the public. However, scholars remain divided over the effectiveness of engaging ordinary Twitter users for mobilizing support online. This article seeks to address this issue by examining whether endorsements from political elites influence the tweeting behavior of ordinary users. Using a quasi-experimental design, we analyze an original dataset of tweets made by users who were mentioned (N = 27,634; 36.62 million tweets) and not mentioned (N = 27,672; 16.30 million tweets) by Indian Prime Minister Narendra Modi on 16th March 2019, during his national election campaign. Our analysis reveals that, on average, users mentioned by Modi exhibited a greater increase in tweet activity compared to those not mentioned. However, this surge in activity proved to be only temporary, suggesting that mentions by political elites facilitate immediate mobilization but are not necessarily self-sustaining. Furthermore, no evidence was found of a differential effect based on users’ pre-existing engagement levels. Our findings offer important insights into political leaders’ strategic use of Twitter in campaigns and contribute to the theoretical understanding of Twitter's role in mobilization and interactivity by bringing in diverse perspectives from the Global South.

Using Twitter to fight the COVID-19 pandemic: the case of United States governors

ABSTRACT This study explores how United States governors used Twitter in non-political contexts during the pandemic. We analysed the content and volume of governors’ tweets during the pandemic using semantic network analysis and applied negative binomial regression analysis to identify the variables influencing their Twitter use. No content differences were found among the governors during the pandemic, regardless of party affiliations. Factors such as election wins and competition levels were significantly correlated with tweet volume. Governors prioritize political motives such as reelection over party affiliation on Twitter, using it strategically for political goals and increasing engagement during times of heightened public attention, such as COVID-19.

Is libraries' use of social media ethical? A phenomenographic investigation of Twitter (X) use at the Bodleian Libraries

PurposeSocial media (SM) has been heavily criticised in recent years for its damaging effects on societies globally. Tasked with empowering those same societies, libraries’ continued use of SM is considered ethically contentious. This study presents the findings of a University of Sheffield study that investigated the ethical tension between libraries and their use of SM by aiming to establish whether: (1) libraries’ use of SM is ethically motivated; (2) ethically informed; (3) and compatible with codes of ethics in the Library and Information Science (LIS) sector.Design/methodology/approachA phenomenographic approach was employed to gather and analyse the data for this study, which is drawn from the transcripts of seven online interviews with Bodleian Libraries staff who used Twitter, now X, in a professional capacity.FindingsThree categories of description were identified among participants: (1) Collectivist conception; (2) Settled conception; (3) Questioning conception. The categories are bound by a shared context of conceptualisation made up of a small set of internal and external influences discussed in the interviews which affected all participants to varying degrees.Originality/valueThe findings were used to support the following determinations: (1) Libraries’ use of SM is ethically motivated. (2) Libraries’ use of SM is ethically informed, in part. Due to lack of evidence, no determination was made about whether libraries’ use of SM is compatible with codes of ethics in the LIS sector. Recommendations for LIS professions and professional bodies are offered based on these determinations.

Linking Opinions Shared on Social Media About COVID-19 Public Health Measures to Adherence: Repeated Cross-Sectional Surveys of Twitter Use in Canada.

The effectiveness of public health measures (PHMs) depends on population adherence. Social media were suggested as a tool to assess adherence, but representativeness and accuracy issues have been raised. The objectives of this repeated cross-sectional study were to compare self-reported PHM adherence and sociodemographic characteristics between people who used Twitter (subsequently rebranded X) and people who did not use Twitter. Repeated Canada-wide web-based surveys were conducted every 14 days from September 2020 to March 2022. Weighted proportions were calculated for descriptive variables. Using Bayesian logistic regression models, we investigated associations between Twitter use, as well as opinions in tweets, and self-reported adherence with mask wearing and vaccination. Data from 40,230 respondents were analyzed. As self-reported, Twitter was used by 20.6% (95% CI 20.1%-21.2%) of Canadians, of whom 29.9% (95% CI 28.6%-31.3%) tweeted about COVID-19. The sociodemographic characteristics differed across categories of Twitter use and opinions. Overall, 11% (95% CI 10.6%-11.3%) of Canadians reported poor adherence to mask-wearing, and 10.8% (95% CI 10.4%-11.2%) to vaccination. Twitter users who tweeted about COVID-19 reported poorer adherence to mask wearing than nonusers, which was modified by the age of the respondents and their geographical region (odds ratio [OR] 0.79, 95% Bayesian credibility interval [BCI] 0.18-1.69 to OR 4.83, 95% BCI 3.13-6.86). The odds of poor adherence to vaccination of Twitter users who tweeted about COVID-19 were greater than those of nonusers (OR 1.76, 95% BCI 1.48-2.07). English- and French-speaking Twitter users who tweeted critically of PHMs were more likely (OR 4.07, 95% BCI 3.38-4.80 and OR 7.31, 95% BCI 4.26-11.03, respectively) to report poor adherence to mask wearing than non-Twitter users, and those who tweeted in support were less likely (OR 0.47, 95% BCI 0.31-0.64 and OR 0.96, 95% BCI 0.18-2.33, respectively) to report poor adherence to mask wearing than non-Twitter users. The OR of poor adherence to vaccination for those tweeting critically about PHMs and for those tweeting in support of PHMs were 4.10 (95% BCI 3.40-4.85) and 0.20 (95% BCI 0.10-0.32), respectively, compared to non-Twitter users. Opinions shared on Twitter can be useful to public health authorities, as they are associated with adherence to PHMs. However, the sociodemographics of social media users do not represent the general population, calling for caution when using tweets to assess general population-level behaviors.

Internet addiction in late adolescence: profile and patterns of use

Introduction: Cross-sectional school-based epidemiological survey, conducted in 2016 and 2017, from a representative sample of 15 to 19-year-old students enrolled in the Greater Vitória Metropolitan Region (RMGV-ES), Espírito Santo, Brazil. Objectives: To verify the association between Internet Addiction, sociodemographic characteristics and the pattern of Internet and social media use. Methods: Cross-sectional study with 2293 students. The sociodemographic data of the individuals and information on internet and social media dependence were verified using the Internet Addiction Test (IAT). Frequencies were calculated and Chi-square and Binomial Logistic Regression tests were applied. Results: Internet addiction was associated with adolescents in the early years (p = 0.001), those with less-educated household heads (p = 0.018), and those who spent four or more hours a day surfing the internet (p &lt; 0.001) and those who used the Internet every day of the week (p = 0.004). Internet addiction was also associated with the use of Twitter (p-value = 0.040), subjective reasons for use (p = 0.001) and those who stopped using it for social reasons (p = 0.001). Conclusion: Public policies that envision the education of adolescents and their families, as well as protection focused on the most susceptible individuals, should be developed. Therefore, it is necessary to prevent adolescents from having daily access to the Internet, not exceeding four hours of use, in order to reduce the risk of dependence and protect the individual from this situation.

Ethical issues of social media in Nigeria

This study sought to analyse ethical concerns of social media in Nigeria. The theoretical framework adopted is the Source Credibility Theory. The study employed Critical Discourse Analysis. The population of the study consisted of the top four (4) social networking sites in Nigeria. Out of these, Twitter was purposively selected for its widespread use for youth activism, particularly within the context of the #EndSARS protest; and for being the only social media platform the federal government had temporarily banned for ethical violations. A convenient sample of ten (10) tweets, which included retweets with text and images posted both during and within 18 months after the protest, was used to collect secondary data. Findings demonstrated a mix of ethical and unethical use of Twitter within the context of the protest. The result also revealed that although Twitter is a credible source of information, there were instances of anonymous tweets, which cast some doubts on the credibility of that specific source. The study recommends that beyond social media regulations, there is a need for the promotion of media literacy in Nigeria’s workplaces and educational system. In addition, the form of self-regulation inherent in African ethics should be applied by users of social media to facilitate harmonious communication. This study has made a modest contribution in the area of source credibility theory by proposing a conceptual framework within the context of the study.

Utilization of Twitter as an Educational Tool to Improve Reading Literacy in Indonesian Language Students

Digital power and lack of access to relevant literature. Twitter, as one of the most popular applications in the era of digital culture, can be used as an educational tool to increase the reading literacy of Indonesian language study program students. The integration of Twitter in the learning of Indonesian language study program students can facilitate access to information, increase creativity, develop reading literacy skills, expand social networks, and encourage student participation. The library research method is used to analyze secondary data from published research articles. The research question raised was, "How can the use of Twitter as an educational tool increase reading literacy among Indonesian language study program students in the era of digital culture?" The findings show that the integration of social media, especially through Twitter, can make a positive contribution to Indonesian language learning by utilizing its features to facilitate access to information, increase creativity, develop reading literacy skills, expand social networks, and encourage student participation. Overall, the use of Twitter in Indonesian language learning promises to significantly increase student reading literacy while building engagement, motivation and a strong learning community.