Level Of User Engagement Research Articles

E-commerce and Consumer Behavior

This dissertation examines consumer behavior in the realm of e-commerce, exploring the factors that influence online purchasing decisions and strategies that enhance customer engagement and loyalty. The rise of e-commerce has dramatically shifted consumer behavior, necessitating a deeper understanding of digital shopping dynamics. Through a mixed-method approach combining surveys, interviews, and data analysis from e-commerce platforms, this study investigates key elements like personalization, content marketing, loyalty programs, and trust-building factors. The findings reveal that personalized interactions, quality content, efficient customer service, and transparent policies significantly impact customer loyalty and engagement. The research contributes to the evolving discourse on e-commerce consumer behavior, offering actionable insights for businesses seeking to optimize their online strategies. This study highlights the importance of adapting to digital consumer preferences and leveraging technology to foster long-term customer relationships in the ever-evolving digital marketplace. The research also reveals the impact of social media and influencer as the key drivers for consumer perception and buying behavior. Moreover, it notes that the use of both AI-driven recommendations and customer-generated content can provide even a higher level of user engagement and practically build the consumers’ trust in the brand. Finally, the research calls for the adoption of omni-channel approach, where the channel planning is much about a consistency to meet customers’ needs from online to the physical world.

Artificial Intelligence-Powered Cognitive Behavioral Therapy Chatbots, a Systematic Review

Objective: This review identifies the characteristic features of artificial intelligence (AI) chatbots and their therapeutic effect; assesses their efficacy in treatment of depression, anxiety, and other mental health disorders; and establishes levels of user engagement and satisfaction. Method: Searches were conducted on the PubMed, Embase, MEDLINE, CENTRAL, CINAHL, PsycINFO, and Google Scholar databases using a set of keywords such as, not limited to, AI cognitive behavioral therapy (AI CBT), Youper, Wysa, Woebot, and other related terms. We included studies that were empirical, peer-reviewed, conducted between January 2017 and June 2024, and primarily focused on efficacy regarding the interventions and therapeutic outcomes. Data were then extracted and analyzed using both qualitative and quantitative methods concerning the mental health outcome. Results: Our review identified large improvements across the three chatbots in symptoms of mental health, as supported by the 10 included studies: five on Woebot, four on Wysa, and one on Youper. Woebot showed remarkable reductions in depression and anxiety with high user engagement; Wysa demonstrated similar improvements, especially in users with chronic pain or maternal mental health challenges; Youper also presented a significant symptom reduction, including a 48% decrease in depression and a 43% decrease in anxiety. Common benefits of all chatbots were the therapeutic alliance and a high rate of satisfaction among users. We have also discussed the included studies’ limitations; that is, study design shortcomings and lack of sample diversity. Conclusion: AI CBT chatbots, including but not limited to Woebot, Wysa, and Youper, are highly promising because of their availability and effectiveness in mental health support. They provide a useful complement to standard therapy when professional help is unavailable, and offer constant engagement with tailored interventions. However, it is necessary that further studies investigate their potential impact as long-term intervention models and explore how they may be integrated into holistic mental health care systems.

Digital Marketing Strategy Through Social Media: Analysis of the Effectiveness of Health Seminar Promotion on Instagram Account @Indonesianmedicalcenter

This study evaluates the efficacy of digital marketing strategies through social media platforms, focusing on the Instagram account @IndonesianMedicalCenter, in promoting health seminars. With the pervasive influence of social media in contemporary marketing, understanding its effectiveness in health seminar promotion is imperative. Utilizing a quantitative approach and an online survey research design, data were collected from 372 respondents who actively follow @IndonesianMedicalCenter account on Instagram. Purposive sampling technique was employed, allowing researchers to selectively choose respondents deemed most relevant and meaningful for the research. Analysis of the data revealed significant insights into the effectiveness of digital marketing strategies via Instagram. User engagement levels with health seminar promotions were assessed, alongside the influence of promotions on seminar participation and attendance. Additionally, participant perspectives regarding the effectiveness of the promotion were analysed. The findings indicate a noteworthy impact of digital marketing strategies through Instagram on health seminar promotion. Increased user engagement and positive perceptions among participants underscore the effectiveness of social media as a promotional tool for health seminars. The results emphasize the importance of leveraging social media platforms like Instagram for health seminar promotion. Engaging content and clear messaging contribute to increased user engagement and ultimately drive seminar participation. In conclusion, digital marketing strategies through social media, particularly on Instagram (@IndonesianMedicalCenter), emerge as potent tools for promoting health seminars. The findings underscore the significance of utilizing engaging content and clear messaging to enhance user engagement and drive seminar participation. Keywords: Digital marketing strategy, social media, Instagram, promotion, health seminar.

The impact and importance of serious games in maritime education: an empirical application

ABSTRACT Gamification and serious gaming have emerged as alternative approaches in learning and decision-making across various domains. In maritime education and the inland waterways sector, where traditional methods may fall short in engaging learners effectively, the development of tailored serious games presents a unique opportunity. This research assesses the educational value of a serious game designed for the maritime industry and inland waterways. The game was developed through a systematic process involving a literature review, stakeholder consultations, and expert input. The methodology included iterative design, user testing, and feedback collection from participants across various sectors. The game features tasks simulating port operations, equipment handling, and inland navigation, followed by quizzes to reinforce learning. Data analysis was performed to evaluate user engagement, knowledge retention, and satisfaction levels. Evaluation results indicate high user engagement, improved knowledge retention, and participant satisfaction. This research underlines the potential of serious games in maritime education, offering innovative solutions to bridge the gap between theoretical knowledge and practical application, thereby maximizing learning outcomes and preparing individuals comprehensively for the challenges of the maritime industry and inland waterways sector.

Enhancing COVID Quarantine Compliance through GeoFencing Technology

This research paper explores the development of an Android geofencing application designed to enhance compliance with COVID-19 quarantine measures [1,5,7]. As public health authorities faced unprecedented challenges during the pandemic, the need for innovative solutions became paramount.This study investigates the effectiveness of geofencing technology in monitoring quarantine adherence by utilizing location-based services to define geographic boundaries around users' homes. The app aims to provide real-time alerts and data analytics to ensure compliance while addressing privacy concerns. Through a mixed-methods approach, including user surveys and case studies, we evaluate user adoption rates, engagement levels, and overall effectiveness in maintaining quarantine protocols.Recently, numerous containment zones have been established across the nation, categorized into red, orange, and green zones[16,17]. The red zones signify areas with high infection rates, orange zones represent regions with some level of infection, and green zones indicate locations free from infection[19, 20]. This paper primarily addresses the creation of an Android application designed to inform individuals about Covid-19 containment zones and to prevent unauthorized entry into these areas. The application provides real-time updates of the containment zone locations on a Google map. Ultimately, the study contributes to the ongoing discourse on the role of technology in managing public health crises and suggests pathways for future research and development in geofencing applications for disease control.

IBCFaiCDR: Auxiliary data-driven item-based collaborative filtering in cross-domain RSs to address user cold start problem

The adoption of Recommender Systems (RSs) in various services is imperative in the present era. One of the inherent challenge faced by RSs is the user cold start problem (UCS) and it occurs when there is a lack of enough data available for a new user, which restricts the capacity to provide accurate recommendations. Researchers have conducted investigations into the utilization of auxiliary data like social network data, review text, demographic information etc., to augment the RSs ability to learn and understand the user's preferences, with the aim of solving this issue. The provided information is inadequate due to the restricted level of user engagement within the specified domain. The researchers utilize a Cross-Domain RS (CDR) that incorporates information from multiple domains to provide personalized suggestions to users. Item Based Collaborative Filtering (IBCF), which utilizes item-item similarity, is commonly used when dealing with sparse data. The suggested collaborative filtering technique employs IBCF which uses the item similarity obtained with item features. These features are generated by the proposed approach IBCFaiCDR's model, trained on source domain data such as product images and reviews. The efficacy of the proposed approach is assessed using a large dataset from Amazon, consisting of user interactions across many categories. The results on target domain, evaluated using MAE and RMSE, indicate that the inclusion of auxiliary information (image + text) enhances the RS performance for new users.

Predicting user engagement levels through emotion-based gesture analysis of initial impressions

Predicting user engagement levels through emotion-based gesture analysis of initial impressions

Analisis penerapan UI/UX dalam aplikasi media sosial: Dampaknya terhadap keterlibatan pengguna dan loyalitas platform

This research focuses on applying UI/UX design principles in social media applications and analyzing their impact on user engagement and platform loyalty in the long term. With increasing competition among social media platforms, user experience has become a major determining factor in app success. This research explores how UI/UX elements such as efficient navigation structure, consistent visual aesthetics, interface responsiveness, and content personalization play a role in increasing user engagement, time spent on the app, and user intent to return to the platform. Using quantitative and qualitative approaches, data was collected through user surveys and analysis of behavioral data from several leading social media platforms. The research results show that optimal UI/UX design not only significantly influences user engagement levels, but also increases user loyalty, reduces churn rates, and increases retention in the long term. This study provides strategic recommendations for social media application developers in designing interfaces that support sustained engagement and positive user experiences

Electric Vehicles in the Digital Discourse: A Sentiment Analysis of Social Media Engagement for Turkey

The adoption of electric vehicles (EVs) is a critical component of transitioning toward sustainable transportation systems. Understanding public sentiment and engagement regarding EVs is essential for policymakers, industry participants, and scholars to address challenges and opportunities in the EV market effectively. This study conducted a comprehensive analysis of public sentiment and engagement concerning EVs on social media platforms. One thousand posts from Facebook, Instagram, and X were analyzed to provide a cohesive narrative encompassing public opinion toward EVs and offering a roadmap for this disruptive technology’s future. The results indicate a significant level of user engagement, supported by 7,000 collective interactions and an impressive 4,300 shares. Predominantly positive sentiments, comprising 83.2% of the analyzed posts, highlight the widespread optimism regarding EV technology. The discourse encompasses various subjects, including brand preferences, financial implications, infrastructure, and environmental aspects. The insights gleaned from these results are of immense value to policymakers, industry participants, and scholars as they navigate the ever-changing terrain of electric mobility.

Investigating the Contribution of MetaRise in the Metaverse

The metaverse, a virtual shared space created by the convergence of virtually enhanced physical reality and physically persistent virtual space, is revolutionizing digital interactions. MetaRise, a pioneering entity in this domain, has made significant contributions that are propelling the metaverse towards unprecedented levels of user engagement and technological advancement. This paper explores the multifaceted contributions of MetaRise, focusing on its innovations in virtual environments, user experience enhancements, and integration with blockchain technology.

Virtual Reality as a Tool for Public Speaking Training: Assessing Efficacy and Engagement

This study investigates the efficacy and engagement of virtual reality (VR) as a tool for public speaking training. The primary objective is to qualitatively analyze the literature to understand how VR technology can enhance public speaking skills and increase user engagement compared to traditional training methods. The research employs a qualitative literature review methodology, synthesizing findings from academic articles, industry reports, case studies, and empirical studies to provide a comprehensive overview of the current state of knowledge in this field. The literature review methodology involves systematically collecting and analyzing scholarly sources that explore various aspects of VR in public speaking training. The study categorizes the literature into key themes, such as the effectiveness of VR in simulating real-life speaking scenarios, the psychological benefits of using VR for reducing anxiety, and the levels of user engagement and motivation in VR-based training programs. Thematic analysis is used to identify patterns and trends in how VR influences public speaking proficiency and participant engagement. The findings indicate that VR offers a highly immersive and interactive environment that can closely mimic real-life public speaking situations, providing users with valuable practice opportunities. Studies show that VR can significantly reduce public speaking anxiety by allowing users to repeatedly practice in a controlled, virtual setting. Additionally, VR-based training programs are found to be more engaging and motivating for users, leading to higher levels of participation and improved learning outcomes.

Virtual Journeys, Real Engagement: Analyzing User Experience on a Virtual Travel Social Platform

A sustainable smart tourism ecosystem relies on building digital networks that link tourists to destinations. This study explores the potential of web and immersive technologies, specifically the Virtual Romania (VRRO) platform, in enhancing sustainable tourism by redirecting tourist traffic to lesser-known destinations and boosting user engagement through interactive experiences. Our research examines how virtual tourism platforms (VTPs), which include web-based and immersive technologies, support sustainable tourism, complement physical visits, influence user engagement, and foster community building through social features and user-generated content (UGC). An empirical analysis of the VRRO platform reveals high user engagement levels, attributed to its intuitive design and interactive features, regardless of the users’ technological familiarity. Our findings also highlight the necessity for ongoing enhancements to maintain user satisfaction. In conclusion, VRRO demonstrates how accessible and innovative technologies in tourism can modernize travel experiences and contribute to the evolution of the broader tourism ecosystem by supporting sustainable practices and fostering community engagement.

Beyond User Decline: Investigating the Effects of Social Presence and the Dual Role of Social Connectedness in Sustaining Engagement on Social Networking Platforms

Social media platforms are currently grappling with unforeseen difficulties that have hindered their expansion. Previous studies have disclosed that Facebook, one of the most prominent social media sites, has encountered a reduction in its user base. Similarly, other social media platforms have also reported a substantial decline in user numbers and engagement levels, indicating a significant downturn in their popularity. The primary objective of this research is to gain a more comprehensive understanding of the role played by the social presence in human-computer-mediated interactions, specifically in the context of social media. Data from 473 college students from their second to tenth semesters were collected through an online survey. Amos 25 was utilized to test the constructs of the variables of social presence, social connectedness, attitude, and intention to continue using social media. The Hayes Macro Process version 3.5 was used to test the proposed model. The results showed that social connectedness (Con) moderates the effect of social presence and attitude on user intention to continue using social networks. This result extends the body of research on human-computer-mediated interactions by uncovering the role of connectedness in human-computer-mediated interactions and technology adoption.

Topic-based engagement analysis: Focusing on hotel industry Twitter accounts

In a social-media context, brands need to understand how to frame their messages, so that a topic can be quickly recognized, promoting higher levels of user engagement. However, knowledge about the link between content type and its engagement is not sufficiently studied. We first explore hotel Firm-Generated Content (FGC) and its inherent themes using topic modelling; we then use an ad hoc metric to investigate the engagement levels associated with each topic; thirdly, we compare the relevance attached to the topics with their engagement levels. In total, 44,448 corporate tweets from 62 hotel brands were analyzed to identify 14 topics, one of which had not previously been uncovered. Notably, there was a positive correlation with engagement for content related to hotel management activities and, among smaller groups, to sustainability. The results will expand FGC-related investigation within the hotel sector and will be of interest to firms seeking effective communication strategies.

Integrasi Kecerdasan Buatan Dalam Sistem Rekomendasi Produk Untuk E-Commerce

The increasing popularity of e-commerce has driven the development of more sophisticated product recommendation systems to enhance user experience. Within this framework, the incorporation of Artificial Intelligence (AI) has become essential for enhancing the caliber of product suggestions through the examination of user behavioral patterns and product attributes. This paper explores the incorporation of artificial intelligence into e-commerce product recommendation systems. This strategy integrates AI methodologies like machine learning, data mining, and natural language processing (NLP) to produce recommendation systems that are personalized and pertinent. Through in-depth analysis of user data and product information, the system can predict user preferences with higher accuracy, improve user engagement levels, and ultimately increase sales conversions. By combining domain knowledge, technical expertise, and the latest research methodologies, This research offers valuable insights for both e-commerce system developers and artificial intelligence researchers. The integration of artificial intelligence into product recommendation systems represents a critical measure in facilitating growth and fostering innovation within the ever-changing e-commerce landscape.

Patriotism and National Symbols in Russian and Ukrainian Elections

How do political parties leverage patriotic appeals in their online campaigning within the context of autocracies and hybrid regimes? This study delves into the digital campaign strategies deployed by political parties during the most recent legislative elections in Russia (2021) and Ukraine (2019). In light of the armed conflict between Russia-backed separatists and Ukrainian forces in the eastern area of Ukraine, war-related themes and patriotic rhetoric emerged as pivotal concerns for politicians in both countries. The “rally around the flag” phenomenon posits that, in times of crisis, citizens often experience an intensified sense of national identity and patriotic fervor. Consequently, references to patriotism and related topics may evoke positive responses and prove instrumental for politicians during elections, serving to engage, mobilize, and attract voters. Drawing on a manual content analysis of the underlying communication strategies, we assessed whether parties’ reference to patriotic gestures and symbols or their attention to related policy topics (defense, war and military conflicts, and foreign policy and international relations) yielded an increased level of user engagement. Our findings reveal that references to patriotic symbols engendered increased user engagement within the Russian context, albeit without significantly affecting the engagement of Ukrainian voters. The latter tended to exhibit greater engagement with posts addressing defense and foreign policy matters though. Interestingly, Russian parties conspicuously avoided war-related topics, while Ukrainian voters displayed a propensity to penalize such content by generating fewer reactions to it.

An Approach Towards to Real Time AI Desktop Voice Assistant

The advent of artificial intelligence (AI) has revolutionized human-computer interaction, making it more natural and intuitive. This research paper presents the development and implementation of an AI Desktop Voice Assistant designed to enhance productivity and accessibility for users. The voice assistant leverages advanced speech recognition, natural language processing (NLP), and machine learning techniques to understand and execute user commands. Key functionalities include voice-activated application control, web searches, personalized reminders, and real-time information retrieval. Our system integrates with widely-used APIs and services, providing a seamless user experience across various tasks. The paper discusses the architecture of the voice assistant, detailing the integration of components such as the speech recognition engine, NLP models, and the dialogue management system. We explore the challenges encountered during development, including accurate speech recognition in noisy environments and handling ambiguous user commands. Solutions implemented to address these challenges are also presented. Furthermore, we conduct a usability study to evaluate the effectiveness and user satisfaction of the voice assistant. The results indicate a high level of user engagement and satisfaction, demonstrating the practical benefits of incorporating AI-driven voice interfaces into desktop environments. Our findings contribute to the ongoing research in human-computer interaction, suggesting pathways for future enhancements in AI voice assistants..

TalkTrek: Journeying Through the Terrain of Text-based Speech Synthesis

Abstract: This research paper delves into the development and evaluation of TextTalker, an innovative voice-enabled education chatbot designed to enhance learning experiences. TextTalker integrates advanced natural language processing capabilities with voice recognition technology to facilitate seamless interactions between users and educational content. Furthermore, it incorporates a unique feature allowing users to access relevant YouTube videos directly within the chat interface, fostering a multi-modal learning environment. The system's architecture and design are meticulously crafted to ensure user engagement, accessibility, and effectiveness in delivering educational materials. Through a series of usability studies and user feedback analysis, this research evaluates the efficacy of TextTalker in supporting learning objectives and enhancing user satisfaction. The findings reveal promising results, indicating high levels of user engagement and satisfaction with the platform's intuitive interface and diverse learning resources. Moreover, incorporating feedback mechanisms empowers users to contribute to the refinement and enhancement of TextTalker's functionalities, fostering a collaborative learning ecosystem. Overall, TextTalker represents a significant advancement in educational technology, offering a user-centric approach to interactive learning through voice-enabled chatbots integrated with multimedia content delivery and feedback mechanisms

A study of social visibility and engagement of world-renowned libraries on Twitter

PurposeThe purpose of this study is to investigate how libraries use Twitter as a social media platform and examine the tweets they post, including multimedia content such as images and video clips. The study also aims to analyse the relationship between post types and user engagement and evaluate the effects of post features, such as multimedia content, on user engagement.Design/methodology/approachThe methodology of the study involved three phases. In Phase 1, a review of related literature was conducted to develop a holistic approach for the study. In Phase 2, official Twitter handles of selected libraries were identified and verified for authenticity using various methods, including cross-checking with library websites. During Phase 3, data was collected from the Twitter handles. The data was then tabulated and interpreted to achieve the set objectives of the study.FindingsThe paper examined the tweets posted by select libraries on Twitter and their impact on user engagement. The study found that most tweets were related to library resources/collection and announcements, followed by events hosted by libraries. Emotionally inspiring posts and daily facts were also commonly posted. The findings also showed that including images in tweets resulted in higher levels of user engagement than video clips did. The study suggests that incorporating images fosters engagement and boosts retweets, while watching a video takes more effort and time.Practical implicationsThe practical implications of the study can provide insights into the tweets that generate user engagement, which can help libraries tailor their social media strategies to attract and retain more followers. The paper can help libraries measure the success of their social media activities by evaluating user engagement metrics.Originality/valueThe originality/ value of the study lies in its examination of how libraries use Twitter as a social media platform, including the tweets they post and the impact of multimedia content on user engagement. While previous studies have examined the use of social media by libraries, this study focuses specifically on Twitter and provides a detailed analysis of the tweets that generate user engagement.

Research on the Impact of Social Media on Brand Loyalty

This study aims to explore the impact of social media on brand loyalty. By analyzing brand interaction, consumer engagement, and the breadth and depth of information dissemination on social media, this study reveals its impact mechanism on brand cognition, brand relationship, and brand attitude. The study uses web crawler technology to collect interactive data from brand official accounts, and uses descriptive statistical analysis, Pearson correlation analysis, multiple regression analysis, and structural equation model (SEM) for data analysis. The results show that brand interaction significantly improves consumers’ brand cognition, consumer engagement plays an important role in brand relationships, and the breadth and depth of information dissemination help to enhance brand attitudes. These factors work together to significantly improve brand loyalty. This research is fundamental because it proves the fact that brand cognition, brand relationship, and brand attitude have a direct effect on brand loyalty, and brand relationship is, of all factors, the most positive factor which influences brand loyalty. This research not only enriched theoretical studies on brand loyalty but also verified the brand marketing strategy on social media with empirical evidence. Moreover, companies increase their brand loyalty by using a better interactivity platform with the consumers, the width and depth of information passing increase, which results in a rise in the level of user engagement by consumers, and the company can increase its competitive advantage in the market.