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This study, an exploratory research, aims to investigate social media users' expectations of information systems (IS) products that are conceived but not yet launched. It specifically analyses social media data from Twitter about forthcoming smartphones and smartwatches from Apple and Samsung, two firms known for their innovative gadgets.

Tweets related to the following four forthcoming IS products were retrieved from 1st January 2020 to 30th September 2020: (1) Apple iPhone 12 (6,125 tweets), (2) Apple Watch 6 (553 tweets), (3) Samsung Galaxy Z Flip 2 (923 tweets) and (4) Samsung Galaxy Watch Active 3 (207 tweets). These 7,808 tweets were analysed using a combination of the Natural Language Processing Toolkit (NLTK) and sentiment analysis (SentiWordNet).

The online community was quite vocal about topics such as design, camera and hardware specifications. For all the forthcoming gadgets, the proportion of positive tweets exceeded that of negative tweets. The most prevalent sentiment expressed in Apple-related tweets was neutral, but in Samsung-related tweets was positive. Additionally, it was found that the proportion of tweets echoing negative sentiment was lower for Apple compared with Samsung.

This paper is the earliest empirical work to examine the degree to which social media chatter can be used by project managers for IS development projects, specifically for the purpose of end-users' expectation management.

Integrating the uses and gratifications (U&G) theory, the notion of information richness and personal epistemology framework, the purpose of this research is to propose and empirically validate a framework which specifies Internet users' urge to click clickbaits.

The hypotheses in the proposed framework were tested using a between-participants experimental design (N = 204) that manipulated information richness (text-only vs. thumbnail clickbaits).

Curiosity, perceived enjoyment and surveillance were significant predictors of the urge to click. In terms of information richness, the urge to click was higher for thumbnail vis-à-vis text-only clickbaits. IEB (IEB) moderated the relation between the gratification of passing time and the urge to click.

This paper represents one of the earliest attempts to investigate Internet users' urge to click clickbaits. Apart from extending the boundary conditions of the U&G theory, it integrates two other theoretical lenses, namely, the notion of information richness and personal epistemology framework, to develop and empirically validate a theoretical framework.

With the growing trend of omni-channel marketing, brands are increasingly looking to offer a seamless experience to their online fan base by connecting with them across multiple social media platforms. This paper explores the relationship between brand posts' characteristics and popularity for start-ups across four different social media platforms: Facebook, Twitter, Instagram and LinkedIn.

A total of 1,200 social media posts from 10 start-ups were subjected to content analysis. Regression analysis was employed with brand posts' popularity (likes, comments and shares/retweets) as the dependent variable.

The results reveal several nuances in brand post popularity for start-ups across Facebook, Twitter, Instagram and LinkedIn. Antecedents of the popularity measures of likes, comments and shares/retweets also fared differently.

The paper reports one of the earliest empirical studies to better understand how the qualities of brand posts are related to their appeal across multiple social media platforms. It advances the literature on social media marketing and offers insights to social media managers of brands, particularly start-ups, on how to offer smoother customer journeys across numerous digital touchpoints.

The Internet is a breeding ground for rumors. A way to tackle the problem involves the use of counter-rumor messages that refute rumors. This paper analyzes users' intention to follow rumors and counter-rumors as a function of two factors: individuals' risk propensity and messages' prior endorsement.

The paper conducted an online experiment. Complete responses from 134 participants were analyzed statistically.

Risk-seeking users were keener to follow counter-rumors compared with risk-averse ones. No difference was detected in terms of their intention to follow rumors. Users' intention to follow rumors always exceeded their intention to follow counter-rumors regardless of whether prior endorsement was low or high.

This paper contributes to the scholarly understanding of people's behavioral responses when, unknowingly, exposed to rumors and counter-rumors on the Internet. Moreover, it dovetails the literature by examining how risk-averse and risk-seeking individuals differ in terms of intention to follow rumors and counter-rumors. It also shows how prior endorsement of such messages drives their likelihood to be followed.

The paper explores the hitherto elusive question: When users are unknowingly exposed to both a rumor and its counter-rumor, which entry is likely to be followed more than the other? It also takes into consideration the roles played by individuals' risk propensity and messages' prior endorsement.

The purpose of this paper is to explore the use of community question answering sites (CQAs) on the topic of terrorism. Three research questions are investigated: what are the dominant themes reflected in terrorism-related questions? How do answer characteristics vary with question themes? How does users’ anonymity relate to question themes and answer characteristics?

Data include 300 questions that attracted 2,194 answers on the community question answering Yahoo! Answers. Content analysis was employed.

The questions reflected the community’s information needs ranging from the life of extremists to counter-terrorism policies. Answers were laden with negative emotions reflecting hate speech and Islamophobia, making claims that were rarely verifiable. Users who posted sensitive content generally remained anonymous.

This paper raises awareness of how CQAs are used to exchange information about sensitive topics such as terrorism. It calls for governments and law enforcement agencies to collaborate with major social media companies to develop a process for cross-platform blacklisting of users and content, as well as identifying those who are vulnerable.

Theoretically, it contributes to the academic discourse on terrorism in CQAs by exploring the type of questions asked, and the sort of answers they attract. Methodologically, the paper serves to enrich the literature around terrorism and social media that has hitherto mostly drawn data from Facebook and Twitter.

The purpose of this paper is twofold: to build a theoretical model that identifies textual cues to distinguish between authentic and fictitious reviews, and to empirically validate the theoretical model by examining reviews of positive, negative as well as moderate polarities.

Synthesizing major theories on deceptive communication, the theoretical model identifies four constructs – comprehensibility, specificity, exaggeration and negligence – to predict review authenticity. The predictor constructs were operationalized as holistically as possible. To validate the theoretical model, 1,800 reviews (900 authentic + 900 fictitious) evenly spread across positive, negative and moderate polarities were analyzed using logistic regression.

The performance of the proposed theoretical model was generally promising. However, it could better discern authenticity for positive and negative reviews compared with moderate entries.

The paper advances the extant literature by theorizing the textual differences between authentic and fictitious reviews. It also represents one of the earliest attempts to examine nuances in the textual differences between authentic and fictitious reviews across positive, negative as well as moderate polarities.

The purpose of this paper is to analyze user-generated comments posted on social media while live matches were being played during the Cricket World Cup 2015.

Data were collected from Yahoo! Cricket (YC), a website that allows people to submit comments during live matches. The comments were qualitatively analyzed using the grounded theory approach.

The key finding of this paper is that people like to consume live sporting events in an online social setting rather than as isolated individuals. In addition, the use of the grounded theory approach helped uncover several new findings related to people’s use of social media during live matches.

Since this paper studied the case of the Cricket World Cup 2015 and collected data from YC, caution is advocated in generalizing its findings.

Scholarly interest on the use of social media during live sporting events is growing. Building on such works, this paper highlights how user-generated comments posted during the Cricket World Cup 2015 – mostly by individuals within the Indian subcontinent – intersected with broader issues such as culture, identity, politics and religion.

This paper aims to explore Internet users' lived experiences with video ads, both skippable and nonskippable, while watching content on YouTube.

In-depth interviews were conducted with 22 participants.

The participants unanimously expressed dissatisfaction with YouTube ads. The dissatisfaction was directed to the platform but did not spill over to the advertised brand/product. Ethical concerns related to privacy also emerged. Specifically, with respect to nonskippable ads, the participants expressed dislike for forced viewing and explained how they would engage in extraneous activities during the ads. Nonetheless, they appreciated the flexibility offered by skippable ads. They also elaborated on how, why and when they would skip/not skip skippable ads.

The findings are discussed in light of the literature on not only online advertising but also platform switching versus continuance intention, spillover effect, privacy–personalization paradox and visual attention.

The purpose of this paper is to investigate the extent to which textual characteristics of online reviews help identify authentic entries from manipulative ones across positive and negative comments.

A theoretical framework is proposed to identify authentic online reviews from manipulative ones based on three textual characteristics, namely, comprehensibility, informativeness, and writing style. The framework is tested using two publicly available data sets, one comprising positive reviews to hype own offerings, and the other including negative reviews to slander competing offerings. Logistic regression is used for analysis.

The three textual characteristics offered useful insights to identify authentic online reviews from manipulative ones. In particular, the differences between authentic and manipulative reviews in terms of comprehensibility and informativeness were more conspicuous for negative entries. On the other hand, the differences between authentic and manipulative reviews in terms of writing style were more conspicuous for positive entries.

The findings of this paper are somewhat constrained by the scope of the data sets used for analysis.

The paper represents one of the earliest attempts to develop a theoretical framework to identify authentic online reviews. Prior research has shed light on ways to classify reviews as authentic or manipulative. However, literature on specific differences between the two in terms of textual characteristics is relatively limited. Moreover, by suggesting differences between authentic and manipulative reviews across positive and negative comments, the findings offer nuanced insights into a research area that is growing in importance.

The purpose of this paper is to investigate the ways in which effectiveness of answers in Yahoo! Answers, one of the largest community question answering sites (CQAs), is related to question types and answerer reputation. Effective answers are defined as those that are detailed, readable, superior in quality and contributed promptly. Five question types that were studied include factoid, list, definition, complex interactive and opinion. Answerer reputation refers to the past track record of answerers in the community.

The data set comprises 1,459 answers posted in Yahoo! Answers in response to 464 questions that were distributed across the five question types. The analysis was done using factorial analysis of variance.

The results indicate that factoid, definition and opinion questions are comparable in attracting high quality as well as readable answers. Although reputed answerers generally fared better in offering detailed and high-quality answers, novices were found to submit more readable responses. Moreover, novices were more prompt in answering factoid, list and definition questions.

By analysing variations in answer effectiveness with a twin focus on question types and answerer reputation, this study explores a strand of CQA research that has hitherto received limited attention. The findings offer insights to users and designers of CQAs.