Popular Communication Research Articles

The Effects of Phishing Attacks on Mobile Phone Users in Tanzania: A Case of Kariakoo Market, Dar es Salaam

This study aimed at understanding phishing attacks targeting mobile phone users in Tanzania, focusing on the investigation of effects of these attacks on the mobile phone users. The study used technology threat avoidance theory as its theoretical framework. Respondents were selected using a purposive stratified sampling method to ensure diverse representation across various demographics and business sectors. A descriptive research design was employed and traders in Kariakoo market, Dar es Salaam were the target population. A sample size of 394 respondents was chosen and data obtained through structured questionnaires and in-depth interviews. Quantitative data were analyzed using SPSS, while qualitative data were examined with Deedose. The study revealed social, economic, and psychological effects of phishing attacks to mobile phone users in Tanzania. Socially, there was a noticeable decline in trust toward digital communications, leading to altered online behaviors and interactions. Economically, the effects included substantial financial losses and disruptions to business operations, impacting both individuals and organizations. Psychologically, the study found that victims experienced emotional distress, anxiety, and a heightened sense of vulnerability, prompting an increased awareness and caution regarding cyber security practices. The study concluded that phishing attacks posed significant social, economic, and psychological challenges for mobile phone users in Tanzania, with effects varying across different demographic groups. It also revealed that users' age, gender, education, and business sector influenced their susceptibility to phishing attacks, leading to diverse experiences and vulnerabilities within the population. The study recommends implementation of targeted awareness campaigns through popular communication channels, such as social media ads and television, to maximize reach and engagement, especially among younger users who are frequently online.

Frontiers in attributing climate extremes and associated impacts

The field of extreme event attribution (EEA) has rapidly developed over the last two decades. Various methods have been developed and implemented, physical modelling capabilities have generally improved, the field of impact attribution has emerged, and assessments serve as a popular communication tool for conveying how climate change is influencing weather and climate events in the lived experience. However, a number of non-trivial challenges still remain that must be addressed by the community to secure further advancement of the field whilst ensuring scientific rigour and the appropriate use of attribution findings by stakeholders and associated applications. As part of a concept series commissioned by the World Climate Research Programme, this article discusses contemporary developments and challenges over six key domains relevant to EEA, and provides recommendations of where focus in the EEA field should be concentrated over the coming decade. These six domains are: (1) observations in the context of EEA; (2) extreme event definitions; (3) statistical methods; (4) physical modelling methods; (5) impact attribution; and (6) communication. Broadly, recommendations call for increased EEA assessments and capacity building, particularly for more vulnerable regions; contemporary guidelines for assessing the suitability of physical climate models; establishing best-practice methodologies for EEA on compound and record-shattering extremes; co-ordinated interdisciplinary engagement to develop scaffolding for impact attribution assessments and their suitability for use in broader applications; and increased and ongoing investment in EEA communication. To address these recommendations requires significant developments in multiple fields that either underpin (e.g., observations and monitoring; climate modelling) or are closely related to (e.g., compound and record-shattering events; climate impacts) EEA, as well as working consistently with experts outside of attribution and climate science more generally. However, if approached with investment, dedication, and coordination, tackling these challenges over the next decade will ensure robust EEA analysis, with tangible benefits to the broader global community.

A Topic Modeling Approach Towards Understanding the Discourse between Religion and Videogames on Reddit

Today's videogames are often intertwined with profound religious narratives, content, characters, and artifacts - but how do player communities understand the role of religion in games, and what is the impression of believers on the use, portrayal, and representation of the religion they practice? This paper dives deep into this confluence by rigorously analyzing discussions from religion and videogame subreddits that often depict the most popular communication channel for their communities. Following topic modeling, we cluster posts and comments from the three major religious groups and the most popular related videogame subreddits, bringing forth representative cultural sentiments and patterns of players and religious stakeholders. Through this, we discovered 22 distinct sub-themes, further categorized into the three overarching themes of (a) Blasphemous Elements of Videogames, (b) Religion as a Design Space for Videogames, and (c) Videogames for Religious Education and Community Forming.

Countering Social Media Cybercrime Using Deep Learning: Instagram Fake Accounts Detection

An online social media platform such as Instagram has become a popular communication channel that millions of people are using today. However, this media also becomes an avenue where fake accounts are used to inflate the number of followers on a targeted account. Fake accounts tend to alter the concepts of popularity and influence on the Instagram media platform and significantly impact the economy, politics, and society, which is considered cybercrime. This paper proposes a framework to classify fake and real accounts on Instagram based on a deep learning approach called the Long Short-Term Memory (LSTM) network. Experiments and comparisons with existing machine and deep learning frameworks demonstrate considerable improvement in the proposed framework. It achieved a detection accuracy of 97.42% and 94.21% on two publicly available Instagram datasets, with F-measure scores of 92.17% and 89.55%, respectively. Further experiments on the Twitter dataset reveal the effectiveness of the proposed framework by achieving an impressive accuracy rate of 99.42%.

Performance evaluation framework of MQTT client libraries for IoT applications in manufacturing

The Internet of Things (IoT) is a revolutionary technology in the field of manufacturing that enables real-time data communication and control of various industrial sensors and devices. MQTT (Message Queuing Telemetry Transport) is one of the most popular communication protocols for IoT applications which offers lightweight, efficient, and reliable communication. There are several MQTT client libraries available for implementing MQTT communication for IoT applications. The selection of an appropriate client library can significantly impact the performance of an IoT application. This paper presents a performance evaluation framework for MQTT client libraries for IoT applications in the manufacturing industry. This paper aims to create a standardized virtual testing environment to compare the performance of different MQTT client libraries using various test conditions. It offers a structured and standardized methodology for evaluating performance aspects such as latency, scalability, and resource utilization. By systematically evaluating the performance of MQTT client libraries against these metrics, users can make informed decisions while selecting the most appropriate library for their IoT applications. The framework takes into consideration the unique requirements and constraints of manufacturing applications, such as the need for low-latency communication, secure data exchange, and compatibility with resource-constrained devices. Ultimately, this research contributes to the optimization of IoT applications in the manufacturing industry, facilitating the implementation of efficient, reliable, and scalable data communication.

Evolving Trends in Turkish Television Series Research: A Comprehensive Bibliometric Analysis from the Web of Science Database

With TV series exported to about 146 countries, Turkey is the second-largest exporter of TV shows worldwide, behind the United States. Turkish TV series reach millions of viewers in regions such as the Balkans, Middle East, Asia, Latin America, and Europe. Despite the significant role of Turkish TV series in academia and communication studies, such bibliometric investigations have been scarce. This study offers a comprehensive bibliometric analysis of research on Turkish television series within communication and cinema studies, drawing on data from the Web of Science database. This analysis encompassed 79 papers from leading journals. Using the Visualization of Similarities (VOS) viewer program, the data was processed to generate bibliographic display maps. Findings indicated that the initial article titled “Turkish TV series” appeared in 2006, with a marked increase in publications post-2020. “Popular Communication” and “Global Media and Communication” emerged as the most cited journals. The analysis also identified “Turkey”, “Turkish TV series”, and “television” as predominant keywords. Additionally, the United States, the United Kingdom, and Turkey were noted as the most prolific countries in publishing studies with the title “Turkish television series.”

Using the role model approach to optimise caregiver administration of sulfadoxine-pyrimethamine amodiaquine to children aged 3–59 months in Burkina Faso, Chad and Togo: findings from an evaluation

BackgroundSeasonal malaria chemoprevention (SMC) is a World Health Organization-recommended intervention for the prevention of malaria among children at high risk in areas with seasonal transmission. During the coronavirus disease 2019 (COVID-19) pandemic, SMC drug distribution was rapidly adapted to reduce contact and mitigate the risk of transmission between communities and community distributors, with caregivers administering doses. To address the challenges and find local solutions to improve administration and adherence, the role model approach was designed, implemented and evaluated in selected communities of Burkina Faso, Chad and Togo. This paper describes the results of this evaluation.MethodsFocus group discussions were held with primary caregivers in all three countries to understand their perceptions of the approach’s acceptability and feasibility. In Burkina Faso and Togo, household surveys assessed the characteristics of caregivers reached by role model activities. Key indicators on SMC coverage and adherence allowed for an assessment of caregiver engagement outcomes related to participation in activities. Statistical associations between participation in study’s activities and caregiver beliefs related to SMC had been tested.ResultsThe majority of caregivers believed the approach to have a positive effect on drug administration, with most adopting the promoted strategies. Greater involvement of fathers in drug administration and acknowledgement of their joint responsibility was a notable positive outcome. However, several barriers to participation were noted and there was criticism of the group approach. In Burkina Faso and Togo, end-of-round survey results revealed that 98.4% of respondents agreed the approach improved their knowledge and skills in malaria prevention, while 100% expressed a desire to continue practicing the behaviours learned. However, there was a relatively low level of awareness of the approach among communities. Participation was strongly associated with participants’ self-reported belief in ease of remembering to administer, and ease of administering, SMC medicines.ConclusionCaregivers perceived the role model approach to be beneficial in aiding drug administration, with other positive impacts also reported. Replication and scale-up should utilize the most popular communication channels and existing community structures to ensure activities are promoted effectively. A mixture of group and one-on-one approaches should be used where appropriate and feasible.

A DISCOURSE ANALYSIS OF CYBER SOCIALISING INTERACTIONS IN ENGLISH AMONG STUDENTS

The influence of modern technology and engagement in cyber socialising have become a prominent part of modern communication. A new learning pedagogy with proper guidelines is needed to assist users to engage with social networking platforms efficiently. The researcher investigated discourse analysis involving participants to answer questions about both the contextual application of the language, and the functions and results of aspects pertaining to discourse such as diction, cohesion, and metaphors. The researcher employed a quantitative approach in this study. The study randomly sampled 80 students from a University of Technology (UoT) in Gauteng to participate in quantitative discourse analysis of communication using Facebook, WhatsApp and Twitter texts. The methods of data elicitation embraced extracts from Facebook, WhatsApp and Twitter texts provided by 80 participants. Statistics were used to present the findings of the quantitative data which included mainly frequency of certain aspects pertaining to discourse. Data were collected via email and texts were numbered according to the participants. These texts remain anonymous and the identities of the participants were concealed. The study found that the language used on Facebook, WhatsApp and Twitter was characterised by the use of emoji, low register words, code-switching few spelling errors and the modern tendency to shorten words by using clipping and number homophones which are not seen as errors but a unique style of writing. Facebook, WhatsApp and Twitter remain three popular communication sites and discourse surfaces since it is important for users to communicate meaningfully even when using excessive punctuation to indicate excitement and emoji to communicate emotions.

When Learner-Centered Teaching and Learning Goes Online: Zooming into Linear Algebra Tutorials During the Pandemic

AbstractThe COVID-19 pandemic shifted higher education online, drawing attention to synchronous learning and instruction on digital communication platforms. Learner-centered teaching practices in the tertiary level, such as mathematical discussions, have been shown to benefit student learning. The interactions involved in online synchronous mathematical discussions have been studied less. Most research taps into these aspects drawing on students’ academic outcomes and reflective interviews. This study explores instructional practices as they unfold online, with a focus on student-instructor and student-student interactions. We zoom-in to online synchronous teaching and learning processes on a popular communication platform by analyzing Linear Algebra tutorials in the first pandemic year. Using the commognitive framework, we characterize instructional interactions with the construct of a learning-teaching agreement. The analysis resulted in three interactional patterns, where in all cases, the tutorial transformed at some point to the one dominated by the instructor.

Nghiên cứu bài toán phát hiện tin nhắn rác trên thiết bị di động và một số vấn đề gợi mở

Short Message Service-SMS is a popular communication method for us. However, high-tech criminals have used spam SMS to cause scams with serious damage. Up to now, the research community and application developers have proposed solutions to detect spam SMS with high accuracy, but in fact, the number of spam SMSs and the amount of financial loss of mobile users caused by this problem have still increased in recent years. Using the research methods of analysis and synthesis on the typical related work, and the research methods of observation and collection actual data from truthful and confident sources, this paper points out the existing problems of spam SMSs detection and proposes some recommendations for creating more efficient and practical solutions.

Effectiveness of the use of WhatsApp for Dissemination of Ideas of Improved Crop Production Techniques

Across India, WhatsApp groups are not only connecting farmers to their customers in the virtual market, but they’re also creating a network of resources and support for the country’s farmers who need it most. It is one of the world’s most popular communication applications in the 21st century. Therefore, a study on the effectiveness of WhatsApp for the dissemination of agricultural technologies in Paddy Crop was conducted at Krishi Vigyan Kendra, Jabalpur (M.P.), in 2022. An exhaustive WhatsApp user list was prepared from 06 villages: Khiriya Kalan and Kathoda from Panagar block, Badkhera and Dunda from Kundam Block, and Agasi and Ahrora from Sahpura block were selected randomly. Thus, 50 farmers from the three blocks of the district using WhatsApp were selected randomly and grouped to send messages about agricultural aspects. The present study highlights and examines the usefulness of WhatsApp among farmers. The social media–enabled WhatsApp is helping farmers solve farming-related problems more efficiently by making them digitally literate. It can be concluded that by using WhatsApp, farmers can seek information on farm operations and clarify their doubts about agriculture and paddy crop production technology, disease & insect pests, etc. It also saved time and money needed to solve the problems. They perceived in the study that the WhatsApp messages used were clear and satisfactory for them. KVK could have achieved immediate solutions to the farmers on a mass level through this App, and need & time-based services to the farming communities were served. On the level of daily interaction, the WhatsApp groups are successful in providing complete assistance and motivating farmers.

WITHDRAWN: The five-factor model, social network, and social influence in instant messaging groups

Nowadays, instant messaging (IM) software is one of the most popular communication tools. Understanding the complex relationships between individual characteristics and social factors is crucial for enhancing the stickiness of IM groups. This study explores the influence of congenital and acquired factors on the stickiness of IM group users. In fact, this research studied the influence of five-factor model, social network, and social influence on stickiness of IM group users. Structural equation modeling was employed to examine the research hypotheses. The research findings revealed that four key personality traits (such as Extraversion, Neuroticism, Agreeableness, and Conscientiousness) may influence the participation in the IM groups. In terms of social networks, emotional support networks have created an influence on the participation in instant messaging groups. As for the social influence, subjective norms and critical mass may affect the participation in IM groups. The obtained results may provide practical insights for the design and improvement of instant messaging software/applications. Moreover, the government can use the relevant findings to formulate policies and develop feasible administrative objectives.

‘It's mostly an accompaniment to something’

‘It's mostly an accompaniment to something’

Email Spam Classifier

Communication plays a major part in everything be it proficient or individual. Because of its widespread use, accessibility, affordability, and free services, email is a popular communication tool. The rise in email-based attacks is a direct result of email protocol weaknesses as well as the growing volume of electronic commerce and financial activities. One of the main issues with today's Internet is email spam, which can financially harm businesses and bother individual consumers. On the internet, spam emails are the main problem. Spammers find it simple to send emails that are filled with spam. Our inbox is flooded with several pointless emails from spam. We receive an overwhelming volume of spam emails every day, making it difficult and time-consuming for us to distinguish between them. Spam remains a problem despite all the efforts made to eradicate it. Furthermore, even valid emails will be removed from consideration when countermeasures become excessively sensitive. Filtering is one of the key strategies among the methods created to prevent spam. This research aims to explore machine learning algorithms and their application to our data sets. The optimal algorithm for email spam detection is chosen based on its optimal precision and accuracy.

Mediating queer masculinities through alternative music from Palestine

ABSTRACT Queer feminist media studies habitually overlooks how popular communications mediate same-sex sexualities beyond the global northwest. Thinking with this gap, this paper problematises mediated queerness in the Arab world. I use the case study of “alternative” music in Israeli-dominated Palestine to theorise how far (or not) Palestinian vernacular modalities constitute a politics of sexuality above and below—although not necessarily in opposition to—the master-narratives of LGBTQ+ recognition, visibility, and the individual closet that often overshadow global commodity platforms. Drawing on my twenty-eight-month ethnography on “alternative” music in Palestine, I explore how queer-identifying Palestinian musicians use music, drag, and performance videos to self-fashion gender and sexual identities, in the context of dominant, media-friendly visions of queerness on digital networks. Through close reading of Bashar Murad’s 2021 song and video, “maskhara” (mockery), and via interviews and ethnographic data, I argue that music constitutes a shifting politics of sexual (in)visibility in Palestine. Musicians move between visible and invisible queer subject positions, depending on audience, locality, and framing. Expanding the field’s focus on Anglo-American sexual representations, then, the contribution theorises mediated queer cultural worldmaking in contexts of settler-colonisation and militarised occupation.

Enhancing MQTT Security in the Internet of Things with an Enhanced Symmetric Algorithm

The Internet of Things (IoT), which connects billions of gadgets to expedite operations and enhance our lives, has completely changed the way we interact with our environment. With MQTT (Message Queuing Telemetry Transport) emerging as a popular communication protocol within the IoT ecosystem, the vast proliferation of networked devices has, however, presented serious security challenges. In order to strengthen MQTT security, this study suggests using an improved symmetric algorithm.Existing MQTT implementations frequently rely on simple security safeguards, making them susceptible to dangers like data manipulation, eavesdropping, and unauthorised access. Our research presents a novel symmetric algorithm designed to meet the particular needs of MQTT communication as a defence against these weaknesses. In order to protect the confidentiality and integrity of data transferred between IoT devices and brokers, this algorithm provides powerful encryption mechanisms. Additionally, it optimises resource usage to take into account the limitations of IoT devices, which frequently have constrained computational and memory resources.

Detecting attacks on e-mail

E-mail has become a popular communication tool widely used by universities, enterprises and governments. Despite the convenience it brought to people, attacks on e-mail happen very frequently in the range of the world, causing large economic loss and occupying a mass of network bandwidth every year. The hazards from e-mail attacks underline the importance of detecting and resisting spam in an efficient and timely way. Using Python, we built Na¨ıve Bayes (NB) and support vector machine (SVM) filters for emails. The filtering performance of NB and SVM email filters applying different kernel functions was compared and evaluated based on several evaluation indices including accuracy, precision, and total cost ratio (TCR). Also, in order to optimize the filters, the influences of stop words removal, feature numbers and other parameters in the filtering algorithms were monitored.

Clearing the air: evaluating institutions' social media health messaging on wildfire and smoke risks in the US Pacific Northwest.

Wildfire smoke contributes substantially to the global disease burden and is a major cause of air pollution in the US states of Oregon and Washington. Climate change is expected to bring more wildfires to this region. Social media is a popular platform for health promotion and a need exists for effective communication about smoke risks and mitigation measures to educate citizens and safeguard public health. Using a sample of 1,287 Tweets from 2022, we aimed to analyze temporal Tweeting patterns in relation to potential smoke exposure and evaluate and compare institutions' use of social media communication best practices which include (i) encouraging adoption of smoke-protective actions; (ii) leveraging numeric, verbal, and Air Quality Index risk information; and (iii) promoting community-building. Tweets were characterized using keyword searches and the Linguistic Inquiry and Word Count (LIWC) software. Descriptive and inferential statistics were carried out. 44% of Tweets in our sample were authored between January-August 2022, prior to peak wildfire smoke levels, whereas 54% of Tweets were authored during the two-month peak in smoke (September-October). Institutional accounts used Twitter (or X) to encourage the adoption of smoke-related protective actions (82% of Tweets), more than they used it to disseminate wildfire smoke risk information (25%) or promote community-building (47%). Only 10% of Tweets discussed populations vulnerable to wildfire smoke health effects, and 14% mentioned smoke mitigation measures. Tweets from Washington-based accounts used significantly more verbal and numeric risk information to discuss wildfire smoke than Oregon-based accounts (p = 0.042 and p = 0.003, respectively); however, Tweets from Oregon-based accounts on average contained a higher percentage of words associated with community-building language (p < 0.001). This research provides practical recommendations for public health practitioners and researchers communicating wildfire smoke risks on social media. As exposures to wildfire smoke rise due to climate change, reducing the environmental disease burden requires health officials to leverage popular communication platforms, distribute necessary health-related messaging rapidly, and get the message right. Timely, evidence-based, and theory-driven messaging is critical for educating and empowering individuals to make informed decisions about protecting themselves from harmful exposures. Thus, proactive and sustained communications about wildfire smoke should be prioritized even during wildfire "off-seasons."

Analysis of the Role of Social Media as an Educational Media for Preconception Nutrition Education of the Millennial Generation in Purwakarta Regency, Indonesia

Social media is a popular communication medium among the millennial generation. Social media can be used as an educational medium for preconception nutrition education, especially in increasing awareness of the millennial generation regarding the importance of preconception nutrition. This research aims to analyze the role of social media as an educational medium for preconception nutrition education for the millennial generation in Purwakarta Regency, Indonesia. This research uses a qualitative research method with a phenomenological approach. Data collection was carried out through in-depth interviews with 10 millennial generation people in Purwakarta Regency. The research results show that social media plays an important role in increasing the millennial generation's awareness of the importance of preconception nutrition. Social media can be used to provide accurate and up-to-date information about preconception nutrition, and can encourage the millennial generation to be more active in adopting healthy eating patterns before pregnancy.

Regimes of visibility and algorithmic surveillance on digital platforms: operationalizing the thought through images in a collaborative perspective

In this article, I present and analyze the results obtained in the first interview for the ongoing thesis project, which investigates how visibility regimes interfere with the algorithmic surveillance regime of bodies in contemporary times. In an initiative stimulated by the exchanges carried out in the Thematic Group Digital and Popular Communication, promoted by the IX ALAIC Summer School, I propose to connect in a single interview the two methodological fronts addressed: the construction of a collaborative visual atlas in the theoretical wake of archeology of visual knowledge, inspired by Aby Warburg, and conducting semi-structured interviews with collective leaders who question aspects of the capitalist culture of surveillance. To this end, the interviewee was presented with a set of images of artistic works related to the themes of body visibility and algorithmic surveillance. The data obtained brought up three thematic nodes: 1) Historical struggles, 2) Countercolonial cosmovisions, and 3) Thinking of images in opposition, which will be analyzed in resonance with the reflections of the authors Antônio Bispo do Rosário, Tarcízio Silva, and Kate Crawford.