Message Characteristics Research Articles

SlimMe, a Chatbot With Artificial Empathy for Personal Weight Management: System Design and Finding.

As the obesity rate continues to increase persistently, there is an urgent need to develop an effective weight loss management strategy. Nowadays, the development of artificial intelligence (AI) and cognitive technologies coupled with the rapid spread of messaging platforms and mobile technology with easier access to internet technology offers professional dietitians an opportunity to provide extensive monitoring support to their clients through a chatbot with artificial empathy. This study aimed to design a chatbot with artificial empathic motivational support for weight loss called “SlimMe” and investigate how people react to a diet bot. The SlimMe infrastructure was built using Dialogflow as the natural language processing (NLP) platform and LINE mobile messenger as the messaging platform. We proposed a text-based emotion analysis to simulate artificial empathy responses to recognize the user's emotion. A preliminary evaluation was performed to investigate the early-stage user experience after a 7-day simulation trial. The result revealed that having an artificially empathic diet bot for weight loss management is a fun and exciting experience. The use of emoticons, stickers, and GIF images makes the chatbot response more interactive. Moreover, the motivational support and persuasive messaging features enable the bot to express more empathic and engaging responses to the user. In total, there were 1,007 bot responses from 892 user input messages. Of these, 67.38% (601/1,007) of the chatbot-generated responses were accurate to a relevant user request, 21.19% (189/1,007) inaccurate responses to a relevant request, and 10.31% (92/1,007) accurate responses to an irrelevant request. Only 1.12% (10/1,007) of the chatbot does not answer. We present the design of an artificially empathic diet bot as a friendly assistant to help users estimate their calorie intake and calories burned in a more interactive and engaging way. To our knowledge, this is the first chatbot designed with artificial empathy features, and it looks very promising in promoting long-term weight management. More user interactions and further data training and validation enhancement will improve the bot's in-built knowledge base and emotional intelligence base.

Why Is Right-Wing Media Consumption Associated With Lower Compliance With COVID-19 Measures?

Abstract. Exposure to right-wing media has been shown to be related to lower perceived threat from COVID-19, lower compliance with prophylactic measures against it, and higher incidence of infection and death. What features of right-wing media messages may account for these effects? In a preregistered cross-sectional study ( N = 554), we tested a model that differentiates perceived consequences of two CDC (Centers for Disease Control and Prevention) recommendations – washing hands and staying home – for basic human values. People who consumed more right-wing media perceived these behaviors as less beneficial for their personal security, for the well-being of close ones, and the well-being of society at large. Perceived consequences of following the CDC recommendations mediated the relationship between media consumption and compliance with recommendations. Implications for public health messaging are discussed.

User- and Message-Level Correlates of Endorsement and Engagement for HIV-Related Messages on Twitter: Cross-sectional Study.

BackgroundYouth and young adults continue to experience high rates of HIV and are also frequent users of social media. Social media platforms such as Twitter can bolster efforts to promote HIV prevention for these individuals, and while HIV-related messages exist on Twitter, little is known about the impact or reach of these messages for this population.ObjectiveThis study aims to address this gap in the literature by identifying user and message characteristics that are associated with tweet endorsement (favorited) and engagement (retweeted) among youth and young men (aged 13-24 years).MethodsIn a secondary analysis of data from a study of HIV-related messages posted by young men on Twitter, we used model selection techniques to examine user and tweet-level factors associated with tweet endorsement and engagement.ResultsTweets from personal user accounts garnered greater endorsement and engagement than tweets from institutional users (aOR 3.27, 95% CI 2.75-3.89; P<.001). High follower count was associated with increased endorsement and engagement (aOR 1.05, 95% CI 1.04-1.06; P<.001); tweets that discussed STIs garnered lower endorsement and engagement (aOR 0.59, 95% CI 0.47-1.74; P<.001).ConclusionsFindings suggest practitioners should partner with youth to design and disseminate HIV prevention messages on social media, incorporate content that resonates with youth audiences, and work to challenge stigma and foster social norms conducive to open conversation about sex, sexuality, and health.

Social Scripts and Expectancy Violations: Evaluating Communication with Human or AI Chatbot Interactants

ABSTRACT As artificial intelligence (AI) agents like chatbots play larger roles in daily life, questions arise regarding how people evaluate their communication. Perspectives applying communication scripts to human-AI interactions propose that outcomes are determined by messages and the embedded cues therein. The expectancy violations perspective posits that message characteristics are less important than whether they are expected or unexpected. A pilot study established baseline expectancies about humans’ and chatbots’ conversational contingency and response latencies. A 2 (contingency: more/less contingent responses) × 2 (latency: fast/slow responses) × 2 (communicator identity: human/chatbot) experiment then tested predictions derived from human-human communication scripts and expectancy violations using textual variations in an e-commerce chat. Communicators showing greater conversational contingency and faster responses were most credible, whether they were human or chatbots, but chatbots were consistently less socially attractive than humans. Results show that humans and chatbots are evaluated similarly regarding the functional, but not the relational aspects of communication. There was greater support for the communication script perspective than the expectancy violations perspective regarding interactions with chatbots.

Fanning the flames: understanding viral content after brand transgressions

PurposeThis paper aims to contribute to the emerging body of research on firestorms, specifically on the inflammatory user-generated content (UGC) created in response to brand transgressions. By analyzing and segmenting UGC created and shared in the wake of three different events, the authors identify which type of inflammatory message is most likely to be widely shared; thus, contributing to a possible online firestorm.Design/methodology/approachTweets were collected involving brand transgressions in the retail, fast food and technology space from varying timeframe and diverse media coverage. Then, the tweets were coded for message intention and analyzed with linguistics software to determine the message characteristics and framing. A two-step cluster analysis identified three types of UGC.FindingsThe authors found that message dimensions and the framing of tweets in the context of brand transgressions differed in characteristics, sentiment, call to action and the extent to which the messages were shared. The findings contradict traditional negative word-of-mouth studies involving idiosyncratic service and product failure. During online brand firestorms, rational activism messages with a call to action, generated in response to a firm’s transgression or “sparks,” have a higher likelihood of being shared (virality).Originality/valueThis research provides novel insights into UGC created after brand transgressions. Different types of messages created after these events vary in the extent that they “fan the flames” of the transgression. A message typology and flowchart are provided to assist managers in identifying and responding to three message types: ash, sparks and embers.

Research on ZigBee Device Recognition Based on Software Defined Radio

In order to solve the problem that ZigBee protocol sniffer analysis is based on proprietary chip platform and cannot obtain radio signal characteristics. A ZigBee protocol packet sniffing recognition method based on software defined radio is proposed. This paper proposes a ZigBee recognition method based on software radio, and analyzes the characteristics of ZigBee protocol messages. The software radio receiving flow diagram is designed to extract the captured message features, and the experimental results of neural network, KNN, decision tree and random forest algorithm are compared. Finally, the decision tree + hybrid classifier achieves 93.1% recognition accuracy, which verifies that the ZigBee recognition method based on software radio proposed in this paper has a good effect.

Способы компенсации невербальных средств коммуникации в SMS-общении

Communication, generally, features not just a system in which the interaction takes place, but also a process, ways of communication, which enable creation, transmission and reception of various information. Nowadays, spoken communication is classified as one of the main types of communication; it is premised to use natural non-verbal and verbal channels simultaneously and in a seamless uniformity; written communication, which occurs as communicative activity among communicators by means of texts; non-verbal communication actualized by means of body language (facial expressions, gestures, etc.) and electronic communication – a relatively new way of communication – which, however, is actively penetrating modern life due to the opportunities which it presents. This article attempts to analyze lexical and syntactic units in English text messages, which help addressees to emphasize their emotional state in a written text while writing it; namely it attempts to demonstrate how non-verbal communication means are actualized via electronic communication. The analysis was carried out on the material of the messages in the Singapore variant of the English language – Singlish SMS – from the corpus SMS NUS. The English language is the dominant one in Singapore these days, prevailing over three other state languages: Chinese, Malay and Tamil. It is used in everyday life in interpersonal communication as a lingua franca and serves as a means of international communication and a means of uniting the country. Upon analysis some characteristic features of SMS messages have been identified, such as punctuation marks, pragmatic particles and interjections, expressions making up for registering the emotional state of the text author in writing.

How politicians adapt to new media logic. A longitudinal perspective on accommodation to user-engagement on Facebook

ABSTRACT The expansion of the Internet, especially social media, enables political actors to address voters directly. However, on social media, where user interactions factor into the algorithmically determined relevance of messages and, in turn, their spread, political actors have to use communication features that entice users to interact with their messages. Taking mediatization theory as a starting point, I transferred assumptions about accommodation into the domain of social media. By conducting a content analysis of Facebook posts made by members of the Bundestag, the German Parliament, from 2010 to 2015, I analyzed whether political actors had adapted their communication to social media logic and more often used message features previously demonstrated to increase the number of interactions. Among the results, politicians had increasingly used message features that had previously raised the number of interactions, including new technical opportunities and social affordances on Facebook, whereas their use of established communication strategies had remained relatively stable. At the individual level, politicians with higher status were more likely to incorporate successful strategies, which suggests that accommodation is constrained by available resources.

How communications by AI-enabled voice assistants impact the customer journey

PurposeArtificial intelligence–enabled voice assistants (VAs), such as Amazon's Alexa, Google Assistant, and Apple's Siri, are available in smartphones, smart speakers, and other digital devices and channels. Use of these VAs is growing rapidly and are expected to significantly impact purchase intentions. This article focuses on how the communications enabled and provided by these VAs influence VA evaluations and usage intentions, contingent on the stage of the customer journey.Design/methodology/approachThis paper builds from work on VAs, work on artificial intelligence (AI) and work on communications, to offer a comprehensive and up-to-date understanding of how VA evaluations and usage intentions may be impacted by the communications from VAs, contingent on the stage of the customer journey.FindingsThis paper proposes a model for VA enabled communications impact VA evaluations. It builds from work on VAs, AI, communications, and customer journey management. In the proposed model, VA evaluations are not only impacted by source, message and recipient characteristics (per prior communication models), but also by (1) VA/AI specific features, like perceptions of humanness and perceptions of artificiality, and (2) stage of the customer journey.Practical implicationsThis paper provides guidance to firms, as regards how VA communications may influence VA evaluations and usage intentions. As an initial conjecture, (1) increasing perceptions of humanness, (2) decreasing perceptions of artificiality (3) a better fit between communications style (e.g. abstract vs concrete), and request type (e.g. transactional vs informational) (4) a better fit between VA communications (e.g. information vs banter), and consumer perceptions of the VA (servant vs partner) and (5) a better fit between VA communications and the stage of the customer journey may positively influence VA evaluations and VA usage intentions.Originality/valueThis paper provides a fresh look at the impact of VA communications, clarifying how such communications impact VA evaluations and usage intentions at various stages of the customer journey.

Impact of e-WOM message characteristics on its perceived usefulness in international tourism

Word of Mouth (WOM) is one of the most frequently used term in the modern technology driven society. WOM is a means of direct interaction among consumers, influencing consumption-related decisions. With the massive expansion of internet, social-media and mobile phones, traditional WOM has given way to electronic Word of Mouth (eWOM). The significance of eWOM lies in its availability to a wider range of audience, though scattered geographically, connected virtually. Studies show that eWOM can influence travel-related decisions of potential tourists. Also known as user-generated content (UGC), eWOM available through social media and other similar platforms expands the ability of travellers to gather information, choose destinations and tour related services, understand the experiences of previous travellers and make better choices. Literature evidences show that the impact of eWOM on consumer decision making in tourism is greater than that of traditional face-to-face WOM communication. The objective of this study is to investigate the influence of eWOM message characteristics (MC) on its perceived usefulness (PU) among the consumers, in the context of international tourism. The data was gathered applying a validated survey questionnaire from 833 respondents in the city of Coimbatore, Tamil Nadu.

Embodying Temporality in Response Efficacy: How Coping Appraisal Promotes Preventive Behavioral Engagement During the Ongoing Pandemic

ABSTRACT This study heightens the understanding of response efficacy as a determinant of engagement in preventive behavior during the ongoing COVID-19 pandemic. To achieve a more nuanced conceptualization of response efficacy, this study proposes and examines a time-based coping appraisal framework, drawing upon a part of the extended parallel process model (EPPM). The current study investigates how the temporality of coping response message features work in generating social distancing behavioral intentions and explicates the role of anticipated emotions in this motivational process. Results of the experimental study (N = 584) indicate that proximal future framed coping response message (vs. distant future message) led to greater response efficacy, which in turn led to greater anticipated guilt and pride, and by extension increased social distancing behavioral intentions. Mediation analyses also demonstrated the indirect effects of the temporality conditions (proximal future-oriented message vs. distant future-oriented message) on social distancing intentions through response efficacy, anticipated guilt, and anticipated pride. The theoretical and practical implications of this study are discussed.

Інтервальна модель портрету користувачів тематичної групи з проблем екології у соціальній мережі

Mathematical models of dynamics of efficiency of information social networks are considered in the work. An approach to estimating model parameters is proposed. A number of experimental studies were conducted on the basis of data on the functioning of a special online group Facebook. The indicator of the characteristics of the information message was studied. An interval discrete model in the form of a difference equation is obtained, which describes the dynamics of users' reactions to messages in thematic groups of social networks. On the basis of the conducted experiments, the efficiency of application of the offered model is confirmed

Twitter as a Technical Communication Platform: How IT Companies' Message Characteristics Relate to Online Engagement

Purpose: Twitter is a promising technical communication platform for companies, but a thorough understanding of how it works best is lacking. This study analyzes characteristics of IT companies' technical communication tweets and relates them to users' online engagement (likes, retweets, replies). Three message characteristics were included: content, message elements, and communication strategies.&lt;br/&gt; Method: We collected technical communication tweets posted by four IT companies in two weeks (N = 1,604). We developed a content categorization and also coded the tweets for message elements, communication strategies, and online engagement. Message elements and communication strategies were compared with those used in the companies' corporate and marketing communication tweets. Negative binomial regression analyses were used to map relationships between message characteristics and online engagement.&lt;br/&gt; Results: Ten content types were distinguished, illustrating the versatile nature of technical communication on Twitter. Hyperlinks were the most prominent message element; two types of elements were less prevalent: elements enhancing attractiveness (photos, videos, emojis) and elements connecting to a broader Twitter discourse (hashtags, mentions). Communication strategies did not include community-building tweets; evoking action was most prominent. Several links were found between message characteristics and online engagement: Providing user instructions or updates and feedback opportunities, including photos or videos, and providing one-way information promoted online engagement.&lt;br/&gt; Conclusion: Although Twitter might work differently for technical communication than for other domains, it seems fruitful to add more attractive message elements and explore community-building strategies within technical communication. However, there is also reason to relativize the importance of online engagement indicators for technical communication.

ORIGINAL RESEARCH Virtual Events in the Era of COVID-19: Perspectives From a Virtual Interdisciplinary Wound Care Symposium

BACKGROUND: The coronavirus disease-19 pandemic has created changes in the way medicine is practiced. The move to virtual conferencing to avoid mass gatherings is a significant change to how health care professionals meet, discuss current trends, and share research. METHODS: Data from exit polls conducted after annual wound care symposiums were reviewed. Physicians, nurses, podiatrists, and other health care professionals attended. Respondents were asked to comment and reflect on their experiences of attending a virtual conference. RESULTS: Over 60% of all (N = 283) respondents stated the virtual conference was better than or on par with a live event. Many respondents had attended this live event in person in previous years. Of all respondents, 83% stated that they planned to access conference materials for the 30 days they remained posted after the event. More than 50% of respondents stated they favored the ability to communicate effectively with colleagues via the instant messaging feature offered by the conference. Approximately 80% of respondents stated that they would like to attend this and other conferences virtually in the future. CONCLUSIONS: The shift from in-person to virtual conferences has the potential to remain a significant method of attending health care conferences. Conference organizers are encouraged to consider how they can implement virtual components, including postconference access to materials, to enhance the conference experience. Additional work needs to be done to understand the impact of the virtual format on knowledge retention.

Linguistic Characteristics of Social Media Messages Spreading across Geographic and Linguistic Boundaries

Social media enable messages to be exchanged beyond geographic constraints. Some of the messages could be shared and forwarded by people with different cultural backgrounds across different geographical regions. Studying the content of messages that can reach diverse populations is important for practices such as movement propagation and global marketing. Existing studies mainly investigated the characteristics of messages that are popular, i.e., shared or forwarded by more users. As the diffusion of information is prone to be echoed inside certain geographical and linguistic boundaries, popular messages are not always to be shared and spread across geographical and linguistic boundaries. We investigated the linguistic characteristics of social media messages that can reach and be disseminated by people across nations, and across geographic and linguistic boundaries in the MeToo movement. Specifically, we analyze the diffusion paths of messages according to the geolocation of tweets and conducted statistical analysis to compare the linguistic characteristic of tweets that spread across geographical or linguistic boundaries with those that do not. We focus on the linguistic characteristics from three aspects: ‘emotions’, ‘social relations’, and ‘economics, politics, and religion’. Our findings reveal that popular messages tend to contain more negative emotions, however, messages with negative emotions are unlikely to be disseminated across geographical or linguistic boundaries. On the other hand, messages on economic topics or non-adults’ issues are more probable to be disseminated universally. The findings provide insights on the content that is more probable to be shared and disseminated by people with different cultural backgrounds across geographical regions.

About time! A scoping review of public-facing emergency department wait time displays in Canada.

Waiting is a common experience for patients during an emergency department (ED) visit. While high acuity patients are seen with little delay, low acuity patients may experience dissatisfaction from prolonged wait times. One strategy to improve patient experience involves changing the perception of the wait by providing realistic expectations of wait times using public-facing wait time displays. The primary objective of this study is to quantify the number of Canadian EDs with online wait time displays and describe the features and type of information provided. A systematic online search of all Canadian EDs was completed to identify EDs with public-facing wait time displays. A scoping review was then performed to assess their message characteristics, translations offered, availability of multi-site information, and accessibility features. Data were summarized using descriptive statistics. Sixty (9.3%) of the 647 Canadian EDs identified provide public-facing real-time wait time displays. Thirteen of these (21.7%) were associated with a single proprietary system. Distribution of wait time displays differs across Canada, with a range of zero to 100% of EDs within each province utilizing this communication tool. Common characteristics include "average" wait time (95%), graphical trend data (32%), number of patients waiting (33%), longest wait time (12%), and expected length of stay (10%). Sixty-two percent of wait time displays provide a combination of these methods to inform wait times. Important accessibility features include language translation, compliance with Canadian National Institute for the Blind (CNIB) accessibility guidelines and availability on a mobile application. Currently, there is emerging use of wait time displays in Canada with considerable variability in the information communicated through these tools. Effectiveness of these displays and their content needs to be determined.

Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic

BackgroundSocial media has become an essential tool to implement risk communication, giving health information could gain more exposure by retweeting during the COVID-19 pandemic.MethodsContent analysis was conducted to scrutinize the official (national and provincial) public health agencies’ Weibo posts (n = 4396) to identify features of information sources and message features (structure, style content). The Zero-Inflated Negative Binomial (ZINB) model was adopted to analyze the association between these features and the frequency of the retweeted messages.ResultsResults indicated that features of source and health information, such as structure, style, and content, were correlated to retweeting. The results of IRR further suggested that compared to provincial accounts, messages from national health authorities’ accounts gained more retweeting. Regarding the information features, messages with hashtags#, picture, video have been retweeted more often than messages without any of these features respectively, while messages with hyperlinks received fewer retweets than messages without hyperlinks. In terms of the information structure, messages with the sentiment (!) have been retweeted more frequently than messages without sentiment. Concerning content, messages containing severity, reassurance, efficacy, and action frame have been retweeted with higher frequency, while messages with uncertainty frames have been retweeted less often.ConclusionsHealth organizations and medical professionals should pay close attention to the features of health information sources, structures, style, and content to satisfy the public’s information needs and preferences to promote the public's health engagement. Designing suitable information systems and promoting health communication strategies during different pandemic stages may improve public awareness of the COVID-19, alleviate negative emotions, and promote preventive measures to curb the spread of the virus.

Is implicit communication quantifiable? A corpus-based analysis of British and Italian political tweets

Twitter is nowadays a powerful means of political propaganda. Its effectiveness can be easily appreciated in the large amounts of messages exchanged by politicians every day. This wealth of data, together with the interactive nature of the social medium, provides an ideal basis for the analysis of a striking feature of political messages, i.e., their implicitness, often achieved using presuppositions, among other strategies. The present work proposes a comparative analysis of British and Italian politicians' use of Twitter by focusing on implicit communication (notably, presuppositions) and the pragmatic functions of tweets. Based on a sample of about 400 tweets, our analysis shows that some of these functions tend to associate either with presuppositional or non-presuppositional communicative devices. Moreover, a critical methodological discussion is offered in order to address the main challenges of quantitative corpus-based pragmatics.

Motivating cascade testing for familial hypercholesterolemia: applying the extended parallel process model for clinician communication.

Motivating at-risk relatives to undergo cascade testing for familial hypercholesterolemia (FH) is critical for diagnosis and lifesaving treatment. As credible sources of information, clinicians can assist in family communication about FH and motivate cascade testing uptake. However, there are no guidelines regarding how clinicians should effectively communicate with probands (the first person diagnosed in the family) and at-risk relatives. Individuals and families with FH can inform our understanding of the most effective communications to promote cascade testing. Guided by the extended parallel process model (EPPM), we analyzed the perspectives of individuals and families with FH for effective messaging clinicians can use to promote cascade testing uptake. We analyzed narrative data from interviews and surveys collected as part of a larger mixed-methods study. The EPPM was used to identify message features recommended by individuals and families with FH that focus on four key constructs (severity, susceptibility, response efficacy, self-efficacy) to promote cascade testing. Participants included 22 individuals from 11 dyadic interviews and 98 survey respondents. Participants described prioritizing multiple messages that address each EPPM construct to alert relatives about their risk. They illustrated strategies clinicians could use within each EPPM construct to communicate to at-risk relatives about the importance of pursuing diagnosis via cascade testing and subsequent treatment for high cholesterol due to FH. Findings provide guidance on effective messaging to motivate cascade testing uptake for FH and demonstrates how the EPPM may guide communication with at-risk relatives about genetic risk and motivate cascade testing broadly.

User perceptions of WeChat and WeChat pay in China

Purpose China has been one of these countries that followed glocalization with the establishment of Chinese social media platforms, which adopt global trends and software patterns. WeChat has been a success story that at first emerged as a social communication tool but has extended to include commercial dynamics as well. Hence, this study aims to understand WeChat user’s general perceptions of the WeChat platform as a general social platform and as a commercial business platform. Design/methodology/approach In this study, the sample (n = 400) was obtained from a specific group of people who have had experiences with different WeChat tools and their payment systems. Nonrandom purposive sampling was used by considering its higher probability of representativeness. The online survey that was given to participants through the WeChat groups included 14 questions, in which eight questions are for demographics and general WeChat use, and six questions are for WeChat payment. After descriptive statistical analysis, comparison-based tests were conducted and interpreted accordingly. Findings Overall, the study participants had a high frequency of using WeChat’s messaging and moments features. Moreover, users perceive WeChat and its payment tools as unsecured or not secure enough. However, that perception did not affect their intention to continue adopting the app. Hence, regardless of the unsecure perception, study participants still had high usage of WeChat pay. Originality/value This paper provides an example from China that is known as a high-tech country, and there are a very few studies on the WeChat app despite their high number of users and daily financial transactions.