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Academic social (question and answer) Q&A sites are now utilised by millions of scholars and researchers for seeking and sharing discipline-specific information. However, little is known about the factors that can affect their votes on the quality of an answer, nor how the discipline might influence these factors. The paper aims to discuss this issue.

Using 1,021 answers collected over three disciplines (library and information services, history of art, and astrophysics) in ResearchGate, statistical analysis is performed to identify the characteristics of high-quality academic answers, and comparisons were made across the three disciplines. In particular, two major categories of characteristics of the answer provider and answer content were extracted and examined.

The results reveal that high-quality answers on academic social Q&A sites tend to possess two characteristics: first, they are provided by scholars with higher academic reputations (e.g. more followers, etc.); and second, they provide objective information (e.g. longer answer with fewer subjective opinions). However, the impact of these factors varies across disciplines, e.g., objectivity is more favourable in physics than in other disciplines.

The study is envisioned to help academic Q&A sites to select and recommend high-quality answers across different disciplines, especially in a cold-start scenario where the answer has not received enough judgements from peers.

This study aims to explore the relationship between the content characteristics of destination online reviews and travel intention under three individual circumstances: temporal distance, social distance and experiential distance.

Based on construal-level theory (CLT), this study divides online travel reviews into concrete and abstract reviews. Three experiments were conducted to test the moderating effects of temporal distance, social distance and experiential distance on the influence of review content characteristics on tourists' travel intentions.

The results show that abstract reviews would lead to higher travel intentions than concrete reviews. Furthermore, tourists' travel intentions differed depending on social distance and were significantly affected by reviews posted by reviewers similar to review recipients. In addition, the study contributes by discovering that the moderating effects of temporal distance, social distance and experiential distance were not significant, which differs from most of the previous research conclusions.

This study focused on review content characteristics, which provided a novel perspective for constructing online travel reviews. Furthermore, this research defined the concept of experiential distance in the context of online travel and expanded the research on psychological distance.

The purpose of this study is to determine if the Brazilian electricity sector is differently affected by the characteristics of the content in the regulatory legislation.

For better robustness of the research, the authors analyzed the period from 1995 to 2013, totaling 4,510 observations. To this end, the selection of regulatory legislation was conducted through Markov regime switching. To identify the characteristics of profile and intensity of regulatory content in each legislation, we applied the content analysis technique.

The main findings of this study position this research in the vanguard regarding other research in the area by showing that all regulatory measures whose characteristics denote market profile of strong and medium intensity affect the risk of electric utilities in Brazil. As contribution from this research, it can be hypothesized that for provisional measures/laws events, the profile and intensity of regulatory content are relevant and have different impact on the risk of stocks and, therefore, should be considered in the design and development of public policies.

The paper investigates by means of content analysis, the profile and intensity characteristics of the content present in the regulatory legislation and to present the impact of these characteristics on the risk of the electric energy Sector in Brazil. The research results showed that it is not all regulatory events that impact the stock market. Therefore, regulatory risk estimates must consider the intensity and scope of each legislation, given that legislation with a higher regulatory content that seeks to modify the sector’s operating rules more deeply tends to have a greater impact on the risk of companies that operate in regulated sectors. Therefore, the paper shows originality and evolution for the researchers in the area, with new and significant information.

Social media are channels of communication and relationship between consumers and brands. In this paper, the determinants of consumer engagement in firm-generated content on Facebook are examined in a higher education institutions (HEIs) context.

Data was collected from 1,981 Facebook brand posts of 16 Brazilian HEIs and thoroughly analyzed with seemingly unrelated regression (SUR).

The results indicated that the type of media does not increase the user's engagement. The emotional content, on the other hand, increases the number of likes and shares and not comments. An interaction between dimensions, type of media and content is relevant disclosed to increase engagement metrics, while characteristics related to the day and time of posting are not relevant.

This study analyzes the factors that influence consumer engagement in brand messages published on Facebook, in the context of higher education institutions. Specifically, the authors seek to examine the influence that emanates from the likes, comments and shares: (1) factors related to the type of media (interactivity and liveliness); (2) content-related factors (remuneration, emotional, entertainment and informational); and (3) factors related to posting (day of the week and time of day).

In the context of educational services, social media is increasingly present, remarkably in HEI marketing practices. Previous studies have shown that universities use social media (mainly Facebook) to promote interactivity with students. The study presents the key characteristics of the postings by the HEIs, with an emphasis on the liveliness, the interactivity of the media, and the information content of the posts. It stands out by the examination of the most relevant factors that influence Facebook engagement, and by providing evidence on the strength of the factors related to post features that influence user engagement.

The research contributes to the proposition and empirical test of a predictive model of consumer engagement on Facebook, which can predict engagement in an HEI context.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2020-0242

Leveraging marketer-generated content (MGC) can increase firms' success. However, few studies uncover the effects of MGC-related attributes on consumer engagement in the context of food marketing. This paper aims to explore the influence of MGC characteristics (valence, content types, vividness and interactivity) on consumer engagement.

This study uses WeChat official account data of seven food companies from China and conducts negative binomial regression models.

The findings indicate that different MGC-related characteristics have separate impacts on consumer WeChat engagement. Title valence, transactional title content and title with punctuation vividness negatively affect consumers' consuming engagement. Knowledgeable or entertaining title content and title with interactivity both positively affect consumers' consuming engagement. Moreover, transactional body text content negatively influences consumers' contributing engagement, whereas entertaining body text content shows positive effects. Vivid and interactive MGC body text attributes enhance consumers' contributing engagement behavior.

This study contributes to social media research in food marketplaces and sheds light on the effect of different WeChat MGC characteristics on separate consumer engagement.

Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.

The integration of social media and e-commerce has resulted in a rising phenomenon among individual content providers (ICPs), who used to offer free content, to provide consumers with paid content, such as online courses, Q&As or consultations. Despite the prevalence of ICPs’ content monetization, empirical research has rarely studied its underlying mechanism. This paper examines how the characteristics of free content contributed by ICPs on social media platforms influence their paid content sales, focusing on the perspective of human brand.

The empirical setting is an online knowledge exchange platform, where users are allowed to provide free content (e.g. answers) on the social media platform and launch paid content (e.g. lectures) on the e-commerce platform. A machine learning technique is employed to construct measures for the characteristics of free content, and fixed-effects estimation is presented to confirm which factors have a significant influence on the sales of paid content.

The empirical results show that the quality, diversity and expertness of free content have a significant positive impact on the sales of the ICP-paid content, with the brand popularity of ICP playing a mediating role.

This study is the first attempt to demystify the relationship between content contribution and ICPs’ content monetization from the perspective of human brand. The findings validate the effectiveness of the “Selling by Contribution” strategy and provide valuable insights for ICPs and social media platforms.

The cruise industry has used technology to attract more millennials than ever before. The progression of social media has transformed the way young individuals gather information for their travel decision-making. Hence, this study aims to investigate the effects of the characteristics of social media – Instagram – on millennials’ trust in and attitudes toward social media content and their behavioral intentions.

A self-administered survey was designed to test the study model, and 323 responses collected were deemed valid for main data analysis.

The results revealed that perceived enjoyment of content is a powerful antecedent of trust, attitudes and behavioral intentions. Content quality is a strong predictor of trust but has no meaningful effect on attitudes and behavioral intentions.

Theoretically, this study contributes to the research in the tourism literature on social media and cruise marketing based on integrating into the technology acceptance model, the characteristics of social media content and trust based on commitment-trust theory. This study can help cruise operators use Instagram to influence millennials and suggests significant implications based on social media interactions with millennials.

As academic social Q&A networking websites become more popular, scholars are increasingly using them to meet their information needs by asking academic questions. However, compared with other types of social media, scholars are less active on these sites, resulting in a lower response quantity for some questions. This paper explores the factors that help explain how to ask questions that generate more responses and examines the impact of different disciplines on response quantity.

The study examines 1,968 questions in five disciplines on the academic social Q&A platform ResearchGate Q&A and explores how the linguistic characteristics of these questions affect the number of responses. It uses a range of methods to statistically analyze the relationship between these linguistic characteristics and the number of responses, and conducts comparisons between disciplines.

The findings indicate that some linguistic characteristics, such as sadness, positive emotion and second-person pronouns, have a positive effect on response quantity; conversely, a high level of function words and first-person pronouns has a negative effect. However, the impacts of these linguistic characteristics vary across disciplines.

This study provides support for academic social Q&A platforms to assist scholars in asking richer questions that are likely to generate more answers across disciplines, thereby promoting improved academic communication among scholars.