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Qin, C.; Liu, Y.; Ma, X.; Chen, J.; Liang, H.: Designing for serendipity in online knowledge communities : an investigation of tag presentation formats and openness to experience (2022)
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- Abstract
- Users increasingly acquire, share, and create knowledge in online knowledge communities, making them massive dynamic knowledge repositories that spark inspiration. While online knowledge communities provide powerful searching tools, they ignore the potential of serendipity in fostering knowledge acquisition. Against this backdrop, this research investigates whether serendipity can be stimulated by design features of communities. Specifically, we examine whether different tag presentation formats may promote serendipity. Two hundred seven participants were randomly assigned to our experimental website that displays one of three tag formats. Results show that users experienced serendipity more frequently while using tag trees than tag clouds, followed by tag lists. Moreover, tag formats moderate how openness to experience affects serendipity. Although openness did not influence serendipity across tag formats, further analysis shows that it significantly decreases serendipity for tag lists, but significantly increases serendipity for tag clouds and trees. Theoretically, these results provide an in-depth understanding of serendipity that is contingent on the interaction between community design features and personality (e.g., openness to experience). Practically, these findings demonstrate how interface features (e.g., tag presentation formats) facilitate serendipity, thus informing better design of online knowledge communities to improve the efficiency of knowledge acquisition.
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Chen, J.; Wang, D.; Xie, I.; Lu, Q.: Image annotation tactics : transitions, strategies and efficiency (2018)
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- Abstract
- Human interpretation of images during image annotation is complicated, but most existing interactive image annotation systems are generally operated based on social tagging, while ignoring that tags are insufficient to convey image semantics. Hence, it is critical to study the nature of image annotation behaviors and process. This study investigated annotation tactics, transitions, strategies and their efficiency during the image annotation process. A total of 90 participants were recruited to annotate nine pictures in three emotional dimensions with three interactive annotation methods. Data collected from annotation logs and verbal protocols were analyzed by applying both qualitative and quantitative methods. The findings of this study show that the cognitive process of human interpretation of images is rather complex, which reveals a probable bias in research involving image relevance feedback. Participants preferred applying scroll bar (Scr) and image comparison (Cim) tactics comparing with rating tactic (Val), and they did fewer fine tuning activities, which reflects the influence of perceptual level and users' cognitive load during image annotation. Annotation tactic transition analysis showed that Cim was more likely to be adopted at the beginning of each phase, and the most remarkable transition was from Cim to Scr. By applying sequence analysis, the authors found 10 most commonly used sequences representing four types of annotation strategies, including Single tactic strategy, Tactic combination strategy, Fix mode strategy and Shift mode strategy. Furthermore, two patterns, "quarter decreasing" and "transition cost," were identified based on time data, and both multiple tactics (e.g., the combination of Cim and Scr) and fine tuning activities were recognized as efficient tactic applications. Annotation patterns found in this study suggest more research needs to be done considering the need for multi-interactive methods and their influence. The findings of this study generated detailed and useful guidance for the interactive design in image annotation systems, including recommending efficient tactic applications in different phases, highlighting the most frequently applied tactics and transitions, and avoiding unnecessary transitions.
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Zheng, X.; Chen, J.; Yan, E.; Ni, C.: Gender and country biases in Wikipedia citations to scholarly publications (2023)
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- Date
- 22. 1.2023 18:53:32
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Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019)
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- Date
- 20. 1.2015 18:30:22
