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Emotion is theorized as profoundly related to ethics and moral decision-making, which makes it relevant for communication towards peace efforts. This experimental study examined the effects of conflict-sensitive framing in news stories and online user-generated comments (a form of UGC – user-generated content) that reflected on the events of political violence such as terrorism, as well as civil and international wars. The results showed an association of conflict-sensitive journalism (peace journalism) and negative emotions; decreasing hope and increasing anger and fear. However, the conflict-sensitive UGC showed some positive emotional effects. Empirical results provide an important context and useful evidence to enrich the normative discussions regarding peace journalism. Furthermore, this study is on the frontline of exploring conflict sensitivity in the environment of digital media and UGC. Such research is vital in specifying the potentials and limitations of conflict-sensitive communication in peacemaking and peacebuilding efforts.

It is essential to give full consideration to the potential barriers facing urban parks from their better functions and meeting residents’ needs in terms of collective perception and satisfaction. This paper presents the methods of using social media (Dianping) data to investigate the potential factors affecting people’s satisfaction with urban parks in Shenzhen, China. Textual analysis and sentiment analysis make it feasible to identify the factors influencing people’s experience in parks. By measuring emotions towards these factors, a multiple linear regression model helps to explore the relationships between the factors and people’s satisfaction, and among them, determines the key ones. The results present the nine key factors of urban parks that affect the users’ satisfaction, in addition to the common factors by previous studies including park size, vegetation, recreation facility, landscape visual effect, maintenance of facilities and plants, and environment cleanliness. A series of contextual factors also significantly influence people’s satisfaction, such as sign system, mosquito and air quality. Among these, sign system has the strongest influence. The results increase the understanding of the human-urban park relationship and identify the characteristics of urban parks that facilitate the degree of satisfaction promotion. Our findings may provide the managerial guidelines for planners and decision-makers to optimize people’s imperative qualities of urban life.

This paper intends to solve the limitations of the existing methods to deal with the comments of tourist attractions. With the technical support of Artificial Intelligence (AI), an online comment method of tourist attractions based on text mining model and attention mechanism is proposed. In the process of text mining, the attention mechanism is used to calculate the contribution of each topic to text representation on the topic layer of Latent Dirichlet Allocation (LDA). The Bidirectional Recurrent Neural Network (BiGRU) can effectively capture the temporal relationship and semantic dependence in the text through its powerful sequence modeling ability, thus achieving a more accurate classification of emotional tendencies. In order to verify the performance of the proposed ATT-LDA- Bigelow model, online comments about tourist attractions are collected from Ctrip.com, and users’ emotional tendencies towards different scenic spots are analyzed. The results show that this model has the best emotion classification effect in online comments of scenic spots, with the accuracy and F1 value reaching 93.85% and 93.68% respectively, which is superior to other emotion classification models. The proposed method not only improves the accuracy of sentiment analysis, but also provides strong support for the optimization of tourism recommendation system and provides more comprehensive, objective and accurate tourism information for scenic spot managers and tourism enterprises. This achievement is expected to bring new enlightenment and breakthrough to the research and practice in related fields.

This study examines when and why online comments from different sources and platforms influence a movie's box office receipts over time. Premised on the theory of information search, we hypothesize that consumers are more likely to engage in active search in the early stages of a movie's release due to greater choice uncertainty, and passive attention is more likely to kick in for later stages of a movie's release, as uncertainty decreases. To test the proposed hypotheses, we tracked over 1,500 sources of online expert and consumer reviews for cinematic movies released for an entire year and continuously monitored major social media sites (e.g., Twitter) for comments. We text-mined the comments to elucidate the sentiments and analyzed the data. Confirming our hypotheses, the results showed that expert reviews and pull-based peer comments have a significant influence in early stages of a movie's release, and the effects decrease over time. In contrast, the volume of comments from push-based microblog platforms have a significant influence on later box office receipts. Our research demonstrates that online opinions are not always persuasive and useful, and our findings provide insights into when consumers are likely to pay attention to which types of online opinions.

Massive open online courses (MOOCs) represent a new online course and teaching mode, offering targeted instruction and timely services to learners. They have become a key direction for reforming online education. Although MOOCs have experienced significant growth in recent years, the quality of courses published on platforms varies greatly, and scientific quality evaluation mechanisms are lacking. Existing studies on online course quality have primarily relied on questionnaire survey data. In the online environment, an abundance of comment data on platforms reflects learners’ perceptions of course quality, and an analysis mode based on learning comments can address the limitations of questionnaire surveys effectively. In this study, comment texts from learners on Chinese university MOOC platforms were chosen as research data. The influencing factors of online open-course quality were analyzed using the KANO model combined with the ordinal Logit regression method. Results demonstrate that system features, video production, teaching level of teachers, usefulness of teaching content, and comprehensiveness of teaching content are essential quality factors. Course-supporting information is considered an expectant quality factor. Teachers’ teaching style and course interaction are categorized as engaging quality factors. This study provides valuable insights for improving MOOC quality in Chinese universities.

Scholars often blame the occurrence of aggressive behavior in online discussions on the anonymity of the Internet; however, even on today’s less anonymous platforms, such as social networking sites, users write plenty of aggressive comments, which can elicit a whole wave of negative remarks. Drawing on the social identity and deindividuation effects (SIDE) model, this research conducts a laboratory experiment with a 2 (anonymity vs. no anonymity) × 2 (aggressive norm vs. non-aggressive norm) between-subjects design in order to disentangle the effects of anonymity, social group norms, and their interactions on aggressive language use in online comments. Results reveal that participants used more aggressive expressions in their comments when peer comments on a blog included aggressive wording (i.e., the social group norm was aggressive). Anonymity had no direct effect; however, we found a tendency that users’ conformity to an aggressive social norm of commenting is stronger in an anonymous environment.

PurposeThis study aimed to empirically examine the effectiveness of disclosing user comment history without disclosing personal identity as a nudge policy to refrain users from posting malicious content online.Design/methodology/approachThe authors collected the number of comments and posters from the leading portal website in South Korea, Naver.com. To causally investigate the impacts of the new nudge policy on the number of comments and posters, the authors used the regression discontinuity design (RDD) approach.FindingsThe authors found that the new policy reduced all types of comments, including the number of malicious comments, self-deleted comments and current comments. This resulted in an overall decrease in the total number of posted comments, which is considered a side effect. In addition, the authors found that the effect of the nudge policy, which disclosed user comment history, has a stronger effect on older female users than their counterparts.Originality/valueThe study findings extend the current knowledge on a nudge policy being implemented by a website as a means to reduce malicious online content and how it impacts user content posting behaviors.

Audiences’ purchase intentions are vital to the success of influencers on social media. This research examined how interpersonal attraction enhances parasocial relationships (PSRs) between influencers and audiences on social media, and how such parasocial relationships, in turn, affect audiences’ continuance intention. Interpersonal attraction contains three dimensions: task attraction, social attraction, and physical attraction. The results indicated that the three dimensions of interpersonal attraction significantly affected PSRs. The results also showed that informational influence and perceived credibility strengthened the relationship between PSRs and purchase intentions. Moreover, online comments positively moderated the effect of PSRs on informational influence and perceived credibility. The implications and suggestions for future research are also discussed.

This study uses eye-movement technology to validate the need for online comments to be introduced into the internet rental model and to investigate the factors influencing tenants’ behaviours in the processing of information and decision-making. It has been found that the online review system could significantly increase the rate of house-viewing decisions. Tenants’ decisions were more affected by subjective comments, which were mainly affected byregression behaviours. Gender factors have an impact on information processing, but not on decision-making. The housing type factor does not affect information processing but has a significant effect on decision-making behaviour.

•Online comments influence perceived risk of HPV and HPV vaccination intention.•Narrative comments resulted in higher perceived risk of HPV than descriptive ones.•Perceived risk of HPV fully mediate the effect of comments on vaccination intention.•Narrative comments only made a difference to risk perception if they were negative. News coverage supportive of human papillomavirus (HPV) vaccination is widespread on the Internet. Meanwhile, large numbers of online comments questioning HPV vaccine safety, attacking vaccine manufacturers or providing personal experience of side effects may reduce the persuasion effect. This study explored how and under what conditions such comments influence the behavioral intention of subsequent youth female viewers or readers. We recruited a random sample of 239 Chinese undergraduate female students from different, non-medicine-related disciplines and conducted a 2 (valence of online comments: positive vs. negative) × 2 (presentation of comments: narrative vs. descriptive) between-subjects factorial design study. After carrying two ANOVAs to examine the effects of experimental conditions, we established a simple mediation and a moderated mediation analysis to test hypothesis. Perceived risk of HPV emerged as a significant mediator in the moderated mediation model. Particularly under the negative condition, the narrative (vs. descriptive) comments increased behavioral intention to receive the vaccine (B = −0.20, SE = 0.10, 95% CI = −0.40 to −0.01) while they increased participants’ perceived risk of HPV (B = −0.14, SE = 0.05, 95% CI = −0.27 to −0.06). However, under the positive condition, there was no significant difference in either risk perception or behavioral intention between the effects of narrative and descriptive comments on participants. Online comments do influence participants’ perceived risk of HPV and vaccination intention. Perceived risk of HPV fully mediates the effect of comments on vaccination intention. More importantly, the indirect effect of narrative (vs. descriptive) comments on behavioral intention through risk perception is moderated by the valence of comments, and significant only under the negative comments condition.