The Influence of Type of Implicit EWOM on Purchase Intention

Electronic Word-of-mouth (eWOM) helps shape consumers’ purchasing decisions and companies’ marketing choices. Researchers and practitioners have extensively studied textual or word-based eWOM in online reviews, blogs, e-mails, and product sites. The effect of implicit eWOM, eWOM using paralinguistic cues, on consumer behavior has been infrequently studied even though marketers often seek to use implicit eWOM to influence consumers. On Facebook, the most popular social networking platform in the world, three of the most frequently used forms of implicit eWOM are the emoticon, the emoji, and the GIF. A comparison of the effect of types of implicit eWOM on the purchase intention of eWOM receivers was made in two studies. Four theories, specifically, (Social Presence Theory, Short et al., 1976), Affect as Information Theory, (Clore & Storbeck, 2006), the Elaboration Likelihood Model (Petty & Cacioppo, 1984) and the Foote, Cone, and Belding Grid Model (Vaughn, 1980, 1986), were used to frame the studies. In Study 1, four independent groups were shown product reviews that were text only, text plus emoticon, text plus emoji, or text plus GIF. Half of each group were shown a product review of candy and half were shown a product review of a computer. The products represent different levels of engagement and cognitive/affective processing. Study 2 included four independent groups shown product reviews that were text only or text followed by either an emoticon, an emoji, or a GIF. Each participant was shown reviews of three products (candy, a chair, or a computer), chosen to represent different levels of engagement and cognitive/affective processing. All pairs of groups were compared using an independent groups t-test. No significant increase in purchase intention due to implicit eWOM was found in either study. In two comparisons between text only and 1) text plus emoticon and 2) text plus emoji, purchase intention was higher for the text only review than for the review that included a paralinguistic cue

Cultures in Community Question Answering

CQA services are collaborative platforms where users ask and answer questions. We investigate the influence of national culture on people's online questioning and answering behavior. For this, we analyzed a sample of 200 thousand users in Yahoo Answers from 67 countries. We measure empirically a set of cultural metrics defined in Geert Hofstede's cultural dimensions and Robert Levine's Pace of Life and show that behavioral cultural differences exist in community question answering platforms. We find that national cultures differ in Yahoo Answers along a number of dimensions such as temporal predictability of activities, contribution-related behavioral patterns, privacy concerns, and power inequality.Comment: Published in the proceedings of the 26th ACM Conference on Hypertext and Social Media (HT'15

Nonverbal Communication Reconstruction on Facebook

Facebook provides users comfort in communicating even though they cannot see expressions or any other nonverbal signs, which have been an essential factor in supporting face-to-face communication. Therefore, this research is necessary because the absence of nonverbal communication, especially facial expression, touching, and gesture, renders the communication process between individuals ineffective and uncomfortable, as it was when people first used email to communicate via the internet. Through the study of Computer-Mediated Communication (CMC) perspectives, nonverbal communication, Social Presence Theory and Lack of Social Context Cues theory, this paper will discuss forms of nonverbal communication in the digital era. This study is based on research conducted by researchers using the netnography method and carried out through literature studies. The research was conducted on the Muslim community Bening Society on Facebook because the communication between them is very intense, as required in netnography. The loss of nonverbal communication in interpersonal communication does not, in fact, reduce netizens’ comfort in communicating and interacting. The emergence of digital emoticons and nonverbals is a substitute for nonverbal communication because digital emoticon and nonverbal functions in mediated interpersonal communication are the same as nonverbal communication

Social media marketing across cultures: how does consumer behavior on Facebook brand pages differ between cultures

This dissertation explores the relationship between culture and social media marketing. Differences in consumer behavior on social media are analyzed. Hofstede’s cultural dimensions are employed to predict these differences between cultures. The data was organically gathered from 6750 posts from 225 different Facebook brand pages and 15 different countries. The gathered data included the engagement metrics such as the amount of likes, shares and comments and the various versions of likes such as: love, wow, funny, angry and sad. To the author’s knowledge this is the first study that uses real world organic data to analyze differences between cultures on social media. Descriptive results are displayed through charts and then the statistical significance is measured through linear regressions. Interesting differences were found that could be explained by Hofstede’s dimensions. One of these is that countries low in individualism and/or high in power distance share posts more than comment on them. Also, the use of the funny and wow emoticon responses seems to be related to higher scores on individualism. These findings have theoretical and practical implications. Some academics posit that cultures are converging, and cultural dimensions are becoming obsolete, because of new communication platforms such as social media (Sobol, Cleveland, & Laroche, 2018). Findings from this dissertation imply that Hofstede’s dimensions could still be powerful predictors of some consumer behavior patterns, even on Facebook. Managers could adopt more viral marketing campaigns in countries where posts get shared more and use invitations to tag friends in the opposite countries. Furthermore, they could become more aware of cultural differences in emoticon sentiment that might influence their success and cater to these expectations accordingly.Esta dissertação explora a relação entre cultura e marketing de redes sociais. São analisadas as diferenças entre o comportamento do consumidor nas redes sociais. As dimensões culturais de Hofstede são utilizadas para prever as diferenças entre culturas. Os dados foram recolhidos organicamente de 6750 publicações de 225 diferentes marcas de páginas de Facebook e de 15 países diferentes. Os dados recolhidos incluíram as métricas de engajamento, como número de gostos, partilhas, comentários e as várias versões dos gostos, como: adoro, wow, riso, ira, triste. Para o conhecimento do autor, este é o primeiro estudo que usa dados orgânicos do mundo real para analisar as diferenças entre culturas nas redes sociais. Resultados descritivos são exibidos através de gráficos e, em seguida, a significância estatística é medida através de regressões lineares. Foram encontradas diferenças interessantes que poderiam ser explicadas pelas dimensões de Hofstede. Uma delas é que os países com baixo individualismo e/ou alto em distância ao poder, fazem mais partilha de publicações em vez de comentários. Além disso, o uso de reações como riso e wow parecem estar relacionadas com pontuações mais altas em individualismo. Estas descobertas têm implicações teóricas e práticas. Alguns académicos postulam que as culturas estão a convergir e as dimensões culturais estão a tornarse obsoletas, graças às novas plataformas comunicação como as redes sociais (Sobol, Cleveland, & Laroche, 2018). Os resultados desta dissertação indicam que as dimensões de Hofstede ainda podem ser poderosos indicadores de alguns padrões de comportamento do consumidor, mesmo no Facebook. Os gerentes podem adotar mais campanhas de marketing virais em países onde as publicações são mais partilhadas e usar os convites para identificar amigos em países opostos. Além disso, eles podem tornar-se mais conscientes das diferenças culturais no uso das reações emocionais que podem influenciar mais o seu sucesso e atender de acordo com essas expectativas

Analyzing the Performance of Different Classifier for Detecting Polarity of Customer Reviews

To determine an author's emotional state from their written words is the focus of sentiment analysis, a subfield of NLP. This study focuses on the many techniques used to categorize the text reviews written in natural language according to the viewpoints expressed therein, in order to determine if the widespread behavior is positive, negative, or neutral. Streaming of thoughts and expression of opinion have been facilitated by the proliferation of debate forums, Weblogs, product review sites, e-commerce, and social networking sites. A lot of people's feelings, reviews, and assessments of others' opinions can be found on social media. This research ranks the top classifier for feelings using data derived from online product reviews posted to Twitter. Experimental work on polarity classification with well-known classifiers such as Naive byes, Support vector machine, and Logistic regression for anticipating testimonials was addressed

Aspects of internet security: identity management and online child protection

This thesis examines four main subjects; consumer federated Internet Identity Management (IdM), text analysis to detect grooming in Internet chat, a system for using steganographed emoticons as ‘digital fingerprints’ in instant messaging and a systems analysis of online child protection. The Internet was never designed to support an identity framework. The current username / password model does not scale well and with an ever increasing number of sites and services users are suffering from password fatigue and using insecure practises such as using the same password across websites. In addition users are supplying personal information to vast number of sites and services with little, if any control over how that information is used. A new identity metasystem promises to bring federated identity, which has found success in the enterprise to the consumer, placing the user in control and limiting the disclosure of personal information. This thesis argues though technical feasible no business model exists to support consumer IdM and without a major change in Internet culture such as a breakdown in trust and security a new identity metasystem will not be realised. Is it possible to detect grooming or potential grooming from a statistical examination of Internet chat messages? Using techniques from speaker verification can grooming relationships be detected? Can this approach improve on the leading text analysis technique – Bayesian trigram analysis? Using a novel feature extraction technique and Gaussian Mixture Models (GMM) to detect potential grooming proved to be unreliable. Even with the benefit of extensive tuning the author doubts the technique would match or improve upon Bayesian analysis. Around 80% of child grooming is blatant with the groomer disguising neither their age nor sexual intent. Experiments conducted with Bayesian trigram analysis suggest this could be reliably detected, detecting the subtle, devious remaining 20% is considerably harder and reliable detection is questionable especially in systems using teenagers (the most at risk group). Observations of the MSN Messenger service and protocol lead the author to discover a method by which to leave digitally verifiable files on the computer of anyone who chats with a child by exploiting the custom emoticon feature. By employing techniques from steganography these custom emoticons can be made to appear innocuous. Finding and removing custom emoticons is a non-trivial matter and they cannot be easily spoofed. Identification is performed by examining the emoticon (file) hashes. If an emoticon is recovered e.g. in the course of an investigation it can be hashed and the hashed compared against a database of registered users and used to support non-repudiation and confirm if an individual has indeed been chatting with a child. Online child protection has been described as a classic systems problem. It covers a broad range of complex, and sometimes difficult to research issues including technology, sociology, psychology and law, and affects directly or indirectly the majority of the UK population. Yet despite this the problem and the challenges are poorly understood, thanks in no small part to mawkish attitudes and alarmist media coverage. Here the problem is examined holistically; how children use technology, what the risks are, and how they can best be protected – based not on idealism, but on the known behaviours of children. The overall protection message is often confused and unrealistic, leaving parents and children ill prepared to protect themselves. Technology does have a place in protecting children, but this is secondary to a strong and understanding parent/child relationship and education, both of the child and parent

ChatGPT and Persuasive Technologies for the Management and Delivery of Personalized Recommendations in Hotel Hospitality

Recommender systems have become indispensable tools in the hotel hospitality industry, enabling personalized and tailored experiences for guests. Recent advancements in large language models (LLMs), such as ChatGPT, and persuasive technologies, have opened new avenues for enhancing the effectiveness of those systems. This paper explores the potential of integrating ChatGPT and persuasive technologies for automating and improving hotel hospitality recommender systems. First, we delve into the capabilities of ChatGPT, which can understand and generate human-like text, enabling more accurate and context-aware recommendations. We discuss the integration of ChatGPT into recommender systems, highlighting the ability to analyze user preferences, extract valuable insights from online reviews, and generate personalized recommendations based on guest profiles. Second, we investigate the role of persuasive technology in influencing user behavior and enhancing the persuasive impact of hotel recommendations. By incorporating persuasive techniques, such as social proof, scarcity and personalization, recommender systems can effectively influence user decision-making and encourage desired actions, such as booking a specific hotel or upgrading their room. To investigate the efficacy of ChatGPT and persuasive technologies, we present a pilot experi-ment with a case study involving a hotel recommender system. We aim to study the impact of integrating ChatGPT and persua-sive techniques on user engagement, satisfaction, and conversion rates. The preliminary results demonstrate the potential of these technologies in enhancing the overall guest experience and business performance. Overall, this paper contributes to the field of hotel hospitality by exploring the synergistic relationship between LLMs and persuasive technology in recommender systems, ultimately influencing guest satisfaction and hotel revenue.Comment: 17 pages, 12 figure

Exploring fine-grained sentiment values in online product reviews

We hypothesise that it is possible to determine a fine-grained set of sentiment values over and above the simple three-way positive/neutral/negative or binary Like/Dislike distinctions by examining textual formatting features. We show that this is possible for online comments about ten different categories of products. In the context of online shopping and reviews, one of the ways to analyse consumers' feedback is by analysing comments. The rating of the ???like??? button on a product or a comment is not sufficient to understand the level of expression. The expression of opinion is not only identified by the meaning of the words used in the comments, nor by simply counting the number of ???thumbs up???, but it also includes the usage of capital letters, the use of repeated words, and the usage of emoticons. In this paper, we investigate whether it is possible to expand up to seven levels of sentiment by extracting such features. Five hundred questionnaires were collected and analysed to verify the level of ???like??? and ???dislike??? value. Our results show significant values on each of the hypotheses. For consumers, reading reviews helps them make better purchase decisions but we show there is also value to be gained in a finer-grained sentiment analysis for future commercial website platforms