Pro-environmental behaviors are rooted in values, and understanding the initial values among college students is pivotal in developing educational strategies to improve their pro-environmental behavior. However, most pro-environmental behavior studies fail to consider the social values and personal values as different dimensional or even conflicting values. This study integrated two distinct values, namely perceived social values and perceived personal values, with the technology acceptance model (TAM) to examine how different values shape college students’ pro-environmental behavioral intentions. The proposed model was then empirically validated using survey data from 245 responses from freshmen students at a University in Chongqing. The findings reveal that while perceived social values and perceived personal values are both positively related to behavioral intention, the effect sizes of the former are much larger. Our findings highlight that higher institutions and instructors should continue shaping the prosocial values among college students and create personal values from pro-environmental behavior to reduce the detrimental impact on the environment and achieve sustainability.
Friend recommendation is a fundamental service in both social networks and practical applications, and is influenced by user behaviors such as interactions, interests, and activities. In this study, we first conduct in-depth investigations on factors that affect recommendation results. Next, we design Friend++, a hybrid multi-individual recommendation model that integrates a weighted average method (WAM) into the random walk (RW) framework by seamlessly employing social ties, behavior context, and personal information. In Friend++, the first plus signifies recommending a new friend through network features, while the second plus stands for using node features. To verify our method, we conduct experiments on three social datasets crawled from the Sina microblog system (Weibo). Experimental results show that the proposed method significantly outperforms six baseline methods in terms of recall, precision, F1-measure, and MAP. As a final step, we describe a case study that demonstrates the scalability and universality of our method. Through discussion, we reach a meaningful conclusion: although common interests are more important than user activities in making recommendations, user interactions may be the most important factor in finding the most appropriate potential friends. Keywords multi-individual friend recommendation architecture, behavior context analysis, Intimacy degree, random walk framework, social networks Citation Gong J B, Gao X X, Cheng H, et al. Integrating a weighted-average method into the random walk framework to generate individual friend recommendations.
PurposeDespite the huge potential of social media, its functionality and impact for enhanced risk communication remain unclear. Drawing on dialogic theory by integrating both “speak from power” and “speak to power” measurements, the article aims to propose a systematic framework to address this issue.Design/methodology/approachThe impact of social media on risk communication is measured by the correlation between “speak from power” and “speak to power” levels, where the former primarily spoke to two facets of the risk communication process – rapidness and attentiveness, and the latter was benchmarked against popularity and commitment. The framework was empirically validated with data relating to coronavirus disease (COVID-19) risk communication in 25,024 selected posts on 17 official provincial Weibo accounts in China.FindingsThe analysis results suggest the relationship between the “speak from power” and “speak to power” is mixed rather than causality, which confirms that neither the outcome-centric nor the process-centric method alone can render a full picture of government–public interconnectivity. Besides, the proposed interconnectivity matrix reveals that two provinces have evidenced the formation of government–public mutuality, which provides empirical evidence that dialogic relationships could exist in social media during risk communication.Originality/valueThe authors' study proposed a prototype framework that underlines the need that the impact of social media on risk communication should and must be assessed through a combination of process and outcome or interconnectivity. The authors further divide the impact of social media on risk communication into dialogue enabler, “speak from power” booster, “speak to power” channel and mass media alternative.
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