User Reactions Research Articles

Development of an Industrial Electrical Installation Training Unit

The purpose of this study is to obtain a modular unit for training and instruction in industrial electrical installations as a suitable learning media. This study uses research and development (RD) with ADDIE model, which consists of five phases: analysis, design, development, implementation, and evaluation. The research subject is Diploma 4 student in Department of Electrical Engineering Education, Faculty of Engineering, Universitas Negeri Yogyakarta. The research result as follows. (1) Manufacture of industrial electrical equipment training module products. (2) Application program feasibility for material-related assessment includes content aspects, learning aspects, and efficiency aspects. All aspects of the substantive feasibility study were rated as highly feasible with a score of 94.5 points. Application program feasibility for media professional evaluation includes visual, hardware, usability, and portability aspects. It has an average score of 109.5 on all aspects of the media feasibility test and is categorized as highly feasible. (3) Student user reactions, including learning, visual, hardware, usability, and portability. All aspects of student user response were rated as very good with an average score of 107.1.

Неодобряемые / одобряемые фрагменты современной социальной реальности: неузуальные неономинации

The article presents the study of word-building, semantic, motivational, syntagmatic, and functional characteristics of non-usual neonominations that appeared in 2005 and have been used in Russian-language Internet communication since that time to the present, denoting the objects of social reality that are either approved or disapproved. The performed analysis has made it possible to identify internationalization, intensification, intellectualization and integration as current trends in the creative neologization of this semantic area. The most productive methods of non-usual word formation in the studied lexical subset include blending, lexicalization of an abbreviation, stem truncation; less frequent – holophrasis, graphics, the inclusion of a foreign component in the centaur word; rarely used – reduplication, tmesis, anagram, stepwise way of word formation, pluralization, creation; irrelevant – the emancipation of the morpheme, the spillage of the word. It is shown that a most creative reaction of Internet users is caused by disapproved objects of reality with a variety of rejected socially significant features; their neonominations are used in contexts with a dominant negative average tone. The dominant regular sphere of functioning of neolexemes, which are formed in unusual ways with the semantics of disapproval/approval are such genres of Internet communication as social networks, blogs and forums. Protologisms, even with a transparent internal form and a readable motivation, are rarely conventionalized. Most of the unusual neonominations of unacceptable/acceptable objects of social reality can be attributed to transnominatives, whose nominative purpose is secondary.

Hazardous human–wildlife encounters, risk attitudes, and the value of shark nets for coastal recreation

AbstractShark incidents are rare and graphic events, and their consequences can influence the behavior of beach users, including bathers, to a great extent. These incidents can be thought of as a fearsome risk that may lead decision makers to overreact or respond with inaction. This paper examines the reaction of recreational beach users, including bathers, to changes in the risk of shark incidents. In addition to valuing recreational visits to Durban Beach, South Africa, we study the reaction of beach visitors to a hypothetical scenario in which protective shark nets, deployed in coastal waters to protect bathers, are to be removed. To examine potential heterogeneity of the treatment effect in a travel cost‐contingent behavior model, we develop a semiparametric multivariate Poisson lognormal (MPLN) model to jointly analyze observed and stated visit counts. Results show that removing protective shark nets at Durban beach would decrease recreational visits by more than 20%. Applying the semiparametric MPLN model we further find that both the value of a recreational visit and the predicted change in visitation rates vary as a function of whether recreationists usually enter the water, whether they have heard of previous shark incidents, and their general risk attitude.

Pengaruh Media Sosial Terhadap Brand Awareness Pada Produk Asuransi Takaful Keluarga

From the point of view of the insurance business is a company whose main business is receiving/selling services, transferring risks from other parties, and obtaining profits with various risks among a number of its customers. Sharia life insurance is risk management based on sharia principles to help and protect each other by providing payments based on the death or life of the participant, or other payments to participants or other parties who are entitled at a certain time as stipulated in the agreement, the amount of which has been determined and is based on results of fund management.
 Social media is an online platform that allows users to make social connections and communicate, collaborate, share and express themselves virtually. Social media has changed the way corporate tools and consumer communication strategies are used, especially in the marketing sector. Social media marketing focuses on business efforts to provide content that engages consumers, encourages them to engage with brands on social media platforms, and inspires them to share information.
 One of the most important elements of social media, according to marketers, is creating and maintaining feedback. This is so that through monitoring and feedback, marketers can learn to influence important social dialogue. Social media offers a variety of educational programs, visual exercises, blog articles and other activities that generate comments, allowing marketers to measure and understand user reactions to any content shared on social media.
 One of the factors that can affect a company's brand awareness is the media. Through media, customers can communicate in two ways with each other as well as with businesses and share text, images, audio, and video materials.

Mobilization in the Context of Campaign Functions and Citizen Participation

Mobilization strategies are an essential part of political parties’ campaign communication. By mobilizing voters and supporters, parties promote civic participation in politics, the forms of which have multiplied given the possibilities of user activities on social media. To define their online mobilization strategies, parties have to choose which forms of participation (e.g., voting, donating, or liking or sharing a post) they will seek to mobilize. Understanding mobilization as a communicative appeal to engage audiences in participatory actions, in our study we conceptually linked parties’ mobilizing appeals with three campaign functions—information, interaction, and mobilization—to systematize different types of mobilization. We applied that categorization to the social media campaigns of parties and top candidates in Germany and conducted a manual quantitative content analysis of 1,495 Facebook and 1,088 Instagram posts published in the run-up to the 2021 federal election. Results show that parties primarily mobilized their audiences to vote and seek out more information (e.g., on the party’s website). Although user reactions are generally an important factor of performance on social media, parties mostly avoided calls to like, share, or comment on posts. When compared, the strategies of parties and candidates indicate that mobilization is more the task of parties than of candidates. Differences between Facebook and Instagram can be attributed to the different technical affordances of the platforms. Because Facebook, unlike Instagram, supports clickable links in posts, parties are more likely to encourage users on Facebook to seek out more information online.

Predicting Facebook sentiments towards research

Social media platforms provide users with various ways of interacting with each other, such as commenting, reacting to posts, sharing content, and uploading pictures. Facebook is one of the most popular platforms, and its users frequently share and reshare posts, including research articles. Moreover, the reactions feature on Facebook allows users to express their feelings towards the content they view, providing valuable data for analysis. This study aims to predict the emotional impact of Facebook posts relating to research articles. We collected data on Facebook posts related to various scientific research domains, including Health Sciences, Social Sciences, Dentistry, Arts, and Humanities. We observed Facebook users’ reactions towards research articles and posts and found that ‘Like’ reactions were the most common. We also noticed that research articles from the Dentistry research domain received a lot of ‘Haha’ reactions. We used machine learning models to predict the sentiment of Facebook posts related to research articles. We used features such as the research article’s title sentiment, abstract sentiment, abstract length, author count, and research domain to build the models. We used five classifiers: Random Forest, Decision Tree, K-Nearest Neighbors, Logistic Regression, and Naïve Bayes. The models were evaluated using accuracy, precision, recall, and F-1 score metrics. The Random Forest classifier was the best model for two- and three-class labels, achieving accuracy measures of 86% and 66%, respectively. We also evaluated the feature importance for the Random Forest model and found that the sentiment of the research article’s title is crucial in predicting the sentiment of the Facebook post. This study has substantial implications for public engagement in science-related messages. The emotional reactions of Facebook users towards research articles and posts can provide valuable insights into public engagement in science, and predicting the emotional impact of Facebook posts related to research articles can help researchers understand how the public perceives scientific research. The findings of the study can aid researchers in effectively communicating their research and engaging the public in scientific discourse.

All You Need is Love? An analysis of the election campaign of the Green Party in 2021 on Facebook.

The 2021 federal election in Germany was very different from previous elections. For the first time, the environmental party, The Greens, ran a candidate for chancellor. In addition, the election campaign was increasingly digital due to the Corona pandemic. Citizens increasingly turned to the internet for information. In this context, Facebook was the most used social network for reading, sharing, and discussing political news. This paper examines the Green Party's use of Facebook during the election campaign to identify characteristics of their communication behaviour and user reactions. The empirical investigation is carried out by means of a qualitative content analysis according to Mayring. In the period from 01/04 to 26/09/2021 a total of 251 posts of the Green Party were analysed. The tool Fanpage Karma was used for this purpose. Based on the number of posts, relevant topics of the online election campaign were identified. We also looked at how often and with which reactions users responded to the party's posts. The results of the study show that the 2021 chancellor candidate Annalena Baerbock plays a prominent role. She is mentioned in 30.68% of all posts. In addition, environmental policy, the party's core issue, takes up a comparatively large amount of space with a total of 111 posts (44.22%). Of these, 39.84% deal with climate-related issues. The results of the analysis also show that the party has a broader range of topics. Social issues are mentioned in 38.65% of the posts and the image of being a ‘single-issue party’ is being shed to some extent. It can also be seen that The Greens, who are among the winners of the 2021 election, publish a comparatively low number of posts. At the same time, they receive the second-most ‘Love’ reactions, and the most ‘Loves’ per post. The study shows Facebook's status in the online election campaign of the German environmental party in the 2021 federal election. It provides information about the scope of use and topic setting on the social platform. At the same time, the results show to what extent and with what reactions the posts have been addressed.

Mapping breastfeeding and COVID-19 related content and engagement on Facebook: Results from an online social listening study.

The COVID-19 pandemic has seen evidence and advice evolve quickly. Since the start of the pandemic there has been confusion and concern about breastfeeding and COVID-19, and advice for this group has at times been contradictory. The volume of information on social media has exacerbated this. This study aimed to understand breastfeeding-related COVID-19 information sharing on social media during the global and Australian vaccine roll-out. The CrowdTangle platform was used to source data from December 2020 to December 2021. Posts were categorised to intent and source and mapped to a timeline of pandemic-related events and announcements. Descriptive analysis was used to understand data distribution patterns and qualitative analysis for post-intent. A total of 945 posts were included. Post-interactions ranged from 0 to 6500. Vaccine-related posts were the highest in number and increased over time. Non-profit organisations shared the highest number of posts (n = 241), but interactions were highest with personal and government accounts. Peaks in posts and interactions mapped to key pandemic-related announcements and events. These results describe the breastfeeding and COVID-19 related content shared on Facebook over 13 months, and the associated interactions. Breastfeeding is an important public health issue and breastfeeding women have experienced conflicting and confusing breastfeeding-related information during the COVID-19 pandemic. Better understanding of social media usage, and the monitoring of changes in usage, as an emergency unfolds, can help target communications. This article adds to the evidence in understanding user reactions to COVID-19 related breastfeeding information on social media. SO WHAT?: Social listening is an important part of health communication and infodemic management. Understanding how users react to and engage with COVID-19 related breastfeeding information on social media can help to understand how the general public perceives and responds to health advice and other information being shared.

Analysis and mining of an election-based network using large-scale twitter data: a retrospective study.

The user-generated Twitter data are a rich source of study and research that reflects the various social, economic, political, and other issues affecting people across the world. Analysis of the social interactions among users, who express themselves online, reveals different internal dynamics and provides detailed insights into real-world phenomena. In this paper, the structure and dynamics of the state assembly election-based tweet-reply network have been studied, as generated by Twitter users across the country of India for a period of 6-weeks. We study the flow of Twitter activity pertaining to the West Bengal assembly elections, along with the identification of the hashtags used by the three main political contenders. This information is used to identify the cluster-level dominance in the Twitter network over the 6-weeks of study. It is observed that this cluster dominance information is representative of the actual outcome of the elections, and can be effectively used as a forecasting tool. The collected tweets are used for lexicon-based emotion detection and further analysis. This highlights the reaction of the social media users in response to the events related to the election. It is observed that fear is the dominant emotion, while happiness is scarce in the opinions expressed during the studied duration. Next, the study and analysis of the complete reply-based social networks during weeks 1, 4, and 6 are undertaken. Important political and media actors are identified with standard network-level measures toward determining the efforts put in by the different clusters and individual actors involved in the election to control the network dominance.

A Quantitative Evaluation for Usability under Software Quality Models

Usability evaluation in Human-Computer Interaction (HCI) is done by observing the user's behaviors and reactions while performing a given task. The observers examine users' behaviors while doing assigned tasks and describe their observations in terms of usability. The usability evaluation would depend on the observers' ability or experience. It proceeds qualitatively. We propose a quantitative evaluation, which adopts attributes and metrics from System and Software Quality Requirement and Evaluation(SQuaRE) published by International Standard Organization (ISO). Furthermore, we examine qualitative observations conducted in usability testing and apply our method to make it a quantitative evaluation.

Effect of situational factors (control, convenience, time pressure, and order complexity) on customers’ self-service technology choices

ABSTRACT Despite the increase in the utilization of self-service technology (SST), which has become a significant trend in the service sectors, including food service, the factors affecting consumers’ acceptance of and resistance to SST must still be identified. Thus, this study investigated the reactions of SST users to situational factors, namely control, convenience, time pressure, and order complexity, when ordering, evaluating, and opting for or against the service. The results revealed that the four SST situational factors significantly affected the perceived benefits, while only three (control, convenience, and time pressure) affected the perceived costs. The perceived benefits and costs positively influenced the perceived efficiency, which significantly affected the users’ approach and avoidance behaviors afterward. This study contributes strategic managerial guidelines to service providers who aim to gain competitive advantages in the food service industry via SST.

Supporting Developers in Addressing Human-Centric Issues in Mobile Apps

Failure to consider the characteristics, limitations, and abilities of diverse end-users during mobile app development may lead to problems for end-users, such as accessibility and usability issues. We refer to this class of problems as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">human-centric issues</i> . Despite their importance, there is a limited understanding of the types of human-centric issues that are encountered by end-users and taken into account by the developers of mobile apps. In this paper, we examine what human-centric issues end-users report through Google App Store reviews, what human-centric issues are a topic of discussion for developers on GitHub, and whether end-users and developers discuss the same human-centric issues. We then investigate whether an automated tool might help detect such human-centric issues and whether developers would find such a tool useful. To do this, we conducted an empirical study by extracting and manually analysing a random sample of 1,200 app reviews and 1,200 issue comments from 12 diverse projects that exist on both Google App Store and GitHub. Our analysis led to a taxonomy of human-centric issues that characterises human-centric issues into three-high level categories: App Usage, Inclusiveness, and User Reaction. We then developed machine learning and deep learning models that are promising in automatically identifying and classifying human-centric issues from app reviews and developer discussions. A survey of mobile app developers shows that the automated detection of human-centric issues has practical applications. Guided by our findings, we highlight some implications and possible future work to further understand and better incorporate addressing human-centric issues into mobile app development.

NEUROMARKETING ACTIONS FOR THE DIGITAL PROMOTION OF TOURISM IN CUBA

The alliance between neuroscience and marketing makes it possible to study user reactions to different purchasing stimuli. The descriptive exploratory research had the objective of proposing neuromarketing actions for the tourist promotion of the Cuba destination on the Cubatravel website. Web analytics tools and a survey of digital users were applied on the eye-tracking biometric technique. The qualitative and quantitative were integrated, with multivariate analysis methods. As main results, the portal needs to be improved, essentially its attractiveness, usability and web quality. The proposed action plan was validated by a group of experts from neuroscience, psychology, tourism and informatics, using the Delphi method and the ANOCHI coefficient as very adequate.

The Emotional Impact of COVID-19 News Reporting: A Longitudinal Study Using Natural Language Processing

The emotional impact of the COVID-19 pandemic and ensuing social restrictions has been profound, with widespread negative effects on mental health. We made use of the natural language processing and large-scale Twitter data to explore this in depth, identifying emotions in COVID-19 news content and user reactions to it, and how these evolved over the course of the pandemic. We focused on major UK news channels, constructing a dataset of COVID-related news tweets (tweets from news organisations) and user comments made in response to these, covering Jan 2020 to April 2021. Natural language processing was used to analyse topics and levels of anger, joy, optimism, and sadness. Overall, sadness was the most prevalent emotion in the news tweets, but this was seen to decline over the timeframe under study. In contrast, amongst user tweets, anger was the overall most prevalent emotion. Time epochs were defined according to the time course of the UK social restrictions, and some interesting effects emerged regarding these. Further, correlation analysis revealed significant positive correlations between the emotions in the news tweets and the emotions expressed amongst the user tweets made in response, across all channels studied. Results provide unique insight onto how the dominant emotions present in UK news and user tweets evolved as the pandemic unfolded. Correspondence between news and user tweet emotional content highlights the potential emotional effect of online news on users and points to strategies to combat the negative mental health impact of the pandemic.

Exploring the impact of sentiment on multi-dimensional information dissemination using COVID-19 data in China

The outbreak of information epidemic in crisis events, with the channel effect of social media, has brought severe challenges to global public health. Combining information, users and environment, understanding how emotional information spreads on social media plays a vital role in public opinion governance and affective comfort, preventing mass incidents and stabilizing the network order. Therefore, from the perspective of the information ecology and elaboration likelihood model (ELM), this study conducted a comparative analysis based on two large-scale datasets related to COVID-19 to explore the influence mechanism of sentiment on the forwarding volume, spreading depth and network influence of information dissemination. Based on machine learning and social network methods, topics, sentiments, and network variables are extracted from large-scale text data, and the dissemination characteristics and evolution rules of online public opinions in crisis events are further analyzed. The results show that negative sentiment positively affects the volume, depth, and influence compared with positive sentiment. In addition, information characteristics such as richness, authority, and topic influence moderate the relationship between sentiment and information dissemination. Therefore, the research can build a more comprehensive connection between the emotional reaction of network users and information dissemination and analyze the internal characteristics and evolution trend of online public opinion. Then it can help sentiment management and information release strategy when emergencies occur.

Which Emotions of Social Media Users Lead to Dissemination of Fake News: Sentiment Analysis Towards Covid-19 Vaccine

The use of social media as a news source is quite common today. However, the fact that the news encountered on social media are accepted as true without questioning or checking their validity is one of the main reasons for the dissemination of fake news. For the social media ecosystem, the question arises as to which emotion is more effective in spreading fake news, as the accuracy and validity of the news are under the control of opinions and emotions rather than evidence-based data. From this point of view, our study investigates whether there is a relationship between users’ reaction to the news and the prevalence of the news. In our study, sentiment analysis was conducted on the reactions of Twitter users to fake news about the COVID-19 vaccine between December 31, 2019 and July 30, 2022. To fully assess whether there is a relationship between the reactions and the prevalence of the news, the spread of real news published in the same period in addition to fake news is also taken into consideration. Fake and real news comments, which were selected in different degrees of prevalence from the most to the least, were examined comparatively. In the study, where text mining techniques were used for text pre-processing, analysis was carried out with NLP techniques. In 83% of the fake news datasets and 91% of the overall news datasets considered in the study, negative emotion was more dominant than other emotions, and it was observed that as negative comments increased, fake news spread more as well as real news. While neutral comments have no effect on prevalence, users who comment on fake news for fun significantly increase the prevalence. Finally, to reveal bot activity NLP techniques were applied.

A mixed reality system combining augmented reality, 3D bio-printed physical environments and inertial measurement unit sensors for task planning

Successful surgical operations are characterized by preplanning routines to be executed during actual surgical operations. To achieve this, surgeons rely on the experience acquired from the use of cadavers, enabling technologies like virtual reality (VR) and clinical years of practice. However, cadavers, having no dynamism and realism as they lack blood, can exhibit limited tissue degradation and shrinkage, while current VR systems do not provide amplified haptic feedback. This can impact surgical training increasing the likelihood of medical errors. This work proposes a novel Mixed Reality Combination System (MRCS) that pairs Augmented Reality (AR) technology and an inertial measurement unit (IMU) sensor with 3D printed, collagen-based specimens that can enhance task performance like planning and execution. To achieve this, the MRCS charts out a path prior to a user task execution based on a visual, physical, and dynamic environment on the state of a target object by utilizing surgeon-created virtual imagery that, when projected onto a 3D printed biospecimen as AR, reacts visually to user input on its actual physical state. This allows a real-time user reaction of the MRCS by displaying new multi-sensory virtual states of an object prior to performing on the actual physical state of that same object enabling effective task planning. Tracked user actions using an integrated 9-Degree of Freedom IMU demonstrate task execution This demonstrates that a user, with limited knowledge of specific anatomy, can, under guidance, execute a preplanned task. In addition, to surgical planning, this system can be generally applied in areas such as construction, maintenance, and education.

The Phenomenon of Krotovukha in the Light of Epistemology

The subject of the study was one of the most viral Russian trends of the turn of 2022–2023: krotovukha, a tincture on a dead mole, which attracted attention of not only the Internet users, but also of doctors, restaurateurs, historians, and legislators. The aim of the research was to identify the reasons for active participation in communication on such a topic. It was found that the image of the mole is very much in demand in world culture. This is due to its otherness, its ability to act, to change space, to link the underworld with the mundane. Analysis of a video by an alcohol blogger from Moscow revealed the presence of initiation semantics attached to tasting. These types of publications become a modified version of the ritualised round drinking, as evidenced by patriotic themes and masculine accessories. The name itself already potentially contains the semantics of the familiar, the expressive, and the dearly beloved. A large number of memes demonstrate the strength of user reactions to krotovukha. The most comical effect is produced by stylistic disruption. The incredible effects of the “national” elixir are played off. The duality of perception of the character and the drink made from his body makes the recognisable image variable, polyvalent, and suitable for multiple transformations. The article concludes by noting that the recipe that went viral reflects a belief in sympathetic magic, the ritual power of sacrifice and the cosmogonic significance of the rite – the sacred timing of information dissemination.

Mid-career switch nursing students' perceptions and experiences of using immersive virtual reality for clinical skills learning: A mixed methods study

BackgroundThere has been an increase of mid-career professionals joining nursing. These adult students possess significant expertise in other areas and may benefit substantially in deliberate practice to acquire skills competency using immersive virtual reality (IVR) for clinical procedures before they practise in actual clinical settings. ObjectivesThis study aims to (1) examine the impact of IVR clinical procedures on mid-career switch students in knowledge, game perception and user reaction; (2) to explore the mid-career switch students' perceptions and experiences in using the IVR clinical procedures. DesignA mixed methods feasibility study was used. Setting and participantsThis study was conducted at a university in Singapore with 34 first-year mid-career switch students. MethodsThis study is a single-group pre-test and post-test experimental study on learning clinical procedures using IVR in the home setting. The study took place from September to November 2021. Focus group discussions were conducted and analysed verbatim using thematic analysis. ResultsThe students demonstrated significant improvement of knowledge for subcutaneous insulin, but overall, the increase in combined scores for both intravenous therapy and subcutaneous insulin were not statistically significant. Three overarching themes included: 1) Learning and practice, 2) Challenges and barriers, and 3) Personal attributes. Most of the participants found the experiences to be engaging, relevant, and satisfying. Some reported experiencing giddiness, headache, and lack of familiarity with technologies. ConclusionsIVR simulation can potentially be used as a supplementary learning tool to improve knowledge of clinical procedures in mid-career switch students.

Teaching agile hardware development with an open‐source engineering simulator: An evaluation with industry participants

AbstractEducational games are increasingly used to teach Agile development approaches to practitioners. Most of these training modules simplify the development environment, for example, by using LEGO bricks or playing cards. This oversimplification has been shown to result in limited transferability of learning to industrial practice. Furthermore, there is a lack of teaching modules that specifically address the challenges of applying Agile to physical products. In this paper, we present an open‐source educational game that realistically simulates a hardware development project to teach Agile principles. Over 2 days, participants design, manufacture, and test modifications for a physical wire bending machine within an authentic engineering and production setting. The training mimics the typical roles, processes, and tools of industrial engineering teams to reflect the challenges of Agile hardware development. The module was evaluated with 44 industry professionals regarding perceived learning and user reaction. A combination of quantitative and qualitative methods was used for the experimental evaluation. The results showed a positive learning effect as the participants' average agreement with Agile principles increased through the training. Concerning user reaction, respondents reported a high degree of relevance, interaction, and confidence, indicating that the realistic simulation of the hardware development appropriately balanced the degree of realism with simplicity. The study showcases the opportunities of properly aligning game components to provoke learning situations targeted by the instructors. It contributes to the extant literature by providing a design framework (product, process, setting, and instruction) and open‐source access to the tools used for implementation.