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A web site usually contains a large number of concept entities, each consisting of one or more web pages connected by hyperlinks. In order to discover these concept…
A web site usually contains a large number of concept entities, each consisting of one or more web pages connected by hyperlinks. In order to discover these concept entities for more expressive web site queries and other applications, the web unit mining problem has been proposed. Web unit mining aims to determine web pages that constitute a concept entity and classify concept entities into categories. Nevertheless, the performance of an existing web unit mining algorithm, iWUM, suffers as it may create more than one web unit (incomplete web units) from a single concept entity. This paper presents two methods to solve this problem. The first method introduces a more effective web fragment construction method so as reduce later classification errors. The second method incorporates site‐specific knowledge to discover and handle incomplete web units. Experiments show that incomplete web units can be removed and overall accuracy has been significantly improved, especially on the precision and F1 measures.
The domain of monetary donation is evolving with the combination of professional donation platforms and social network sites (SNSs) in the agency process, potentially…
The domain of monetary donation is evolving with the combination of professional donation platforms and social network sites (SNSs) in the agency process, potentially enhancing information communication and facilitating money transfers between donors and recipients. However, SNS donation avoidance hinders the leveraging of significant economic and social values. To address the limited understanding of the phenomenon of SNS donation avoidance, this study aims to investigate the influencing factors of people's avoidance behavior in the agency process of SNS donation.
A model was devised containing four process-related factors (requests overload, process ambiguity, channel security concerns and perceived distributive injustice) as antecedents of SNS donation avoidance, with probable mediating paths of negative emotions, altruistic outcome expectation and egoistic outcome expectation. Data were collected through a survey of 398 users of WeChat Moment in China. Structural equation modeling was used to analyze the proposed model.
All four process-related factors have positive associations with SNS donation avoidance. Requests overload, channel security concerns and perceived distributive injustice all positively influence people's expectation of negative emotions and lead, in turn, to their SNS donation avoidance. Perceived distributive injustice also leads to SNS donation avoidance via negatively influencing people's expectations of both altruistic and egoistic outcomes.
Theoretically, this empirical study synthetically associates process-related factors to donation avoidance through the paths of emotional responses and rational outcome expectations. Practically, it emphasizes key factors to consider in the process management of SNS donation.