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Lee, M.K.O.; Cheung, C.M.K.; Chen, Z.: Understanding user acceptance of multimedia messaging services : an empirical study (2007)
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- Abstract
- Multimedia Messaging Services (MMS) is a new medium that enriches people's personal communication with their business partners, friends, or family. Following the success of Short Message Services, MMS has the potential to be the next mobile commerce killer application which is useful and popular among consumers; however, little is known about why people intend to accept and use it. Building upon the motivational theory and media richness theory, the research model captures both extrinsic (e.g., perceived usefulness and perceived ease of use) and intrinsic (e.g., perceived enjoyment) motivators as well as perceived media richness to explain user intention to use MMS. An online survey was conducted and 207 completed questionnaires were collected. By integrating the motivation and the media richness perspectives, the research model explains 65% of the variance. In addition, the results present strong support to the existing theoretical links as well as to those newly hypothesized in this study. Implications from the current investigation for research and practice are provided.
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.13, S.2066-2077
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Yan, E.; Chen, Z.; Li, K.: Authors' status and the perceived quality of their work : measuring citation sentiment change in nobel articles (2020)
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- Abstract
- Prior research in status ordering has used numeric indicators to examine the impact of a status change on the perception of a scientist's work. This study measures the perception change directly as reflected in citation sentiment, with the attainment of a Nobel Prize in Chemistry or a Nobel Prize in Physiology or Medicine considered the status change. The article identifies 12,393 citances to 25 Nobel articles in PubMed Central and includes a control article set of 75 articles with 30,851 citances. The results show a moderate increase in citation sentiment toward Nobel articles postaward. Dynamically, for Nobel articles there is a steady sentiment increase, and a Nobel Prize seems to co-occur with this trend. This trend, however, is not evident in the control article set.
- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.3, S.314-324
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Chen, Z.; Huang, Y.; Tian, J.; Liu, X.; Fu, K.; Huang, T.: Joint model for subsentence-level sentiment analysis with Markov logic (2015)
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- Abstract
- Sentiment analysis mainly focuses on the study of one's opinions that express positive or negative sentiments. With the explosive growth of web documents, sentiment analysis is becoming a hot topic in both academic research and system design. Fine-grained sentiment analysis is traditionally solved as a 2-step strategy, which results in cascade errors. Although joint models, such as joint sentiment/topic and maximum entropy (MaxEnt)/latent Dirichlet allocation, are proposed to tackle this problem of sentiment analysis, they focus on the joint learning of both aspects and sentiments. Thus, they are not appropriate to solve the cascade errors for sentiment analysis at the sentence or subsentence level. In this article, we present a novel jointly fine-grained sentiment analysis framework at the subsentence level with Markov logic. First, we divide the task into 2 separate stages (subjectivity classification and polarity classification). Then, the 2 separate stages are processed, respectively, with different feature sets, which are implemented by local formulas in Markov logic. Finally, global formulas in Markov logic are adopted to realize the interactions of the 2 separate stages. The joint inference of subjectivity and polarity helps prevent cascade errors. Experiments on a Chinese sentiment data set manifest that our joint model brings significant improvements.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.9, S.1913-1922
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Shen, D.; Chen, Z.; Yang, Q.; Zeng, H.J.; Zhang, B.; Lu, Y.; Ma, W.Y.: Web page classification through summarization (2004)
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- Source
- SIGIR'04: Proceedings of the 27th Annual International ACM-SIGIR Conference an Research and Development in Information Retrieval. Ed.: K. Järvelin, u.a
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Xu, Y.C..; Chen, Z.: Relevance judgment : what do information users consider beyond topicality? (2006)
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- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.7, S.961-973
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Wenyin, L.; Chen, Z.; Li, M.; Zhang, H.: ¬A media agent for automatically builiding a personalized semantic index of Web media objects (2001)
0.01
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- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.10, S.853-855
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Ren, P.; Chen, Z.; Ma, J.; Zhang, Z.; Si, L.; Wang, S.: Detecting temporal patterns of user queries (2017)
0.01
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- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.1, S.113-128
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Chen, Z.; Wenyin, L.; Zhang, F.; Li, M.; Zhang, H.: Web mining for Web image retrieval (2001)
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- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.10, S.831-839
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Chen, Z.; Meng, X.; Fowler, R.H.; Zhu, B.: Real-time adaptive feature and document learning for Web search (2001)
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- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.8, S.655-665
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Chen, Z.; Fu, B.: On the complexity of Rocchio's similarity-based relevance feedback algorithm (2007)
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- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.10, S.1392-1400
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Cui, C.; Ma, J.; Lian, T.; Chen, Z.; Wang, S.: Improving image annotation via ranking-oriented neighbor search and learning-based keyword propagation (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.1, S.82-98
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Lian, T.; Chen, Z.; Lin, Y.; Ma, J.: Temporal patterns of the online video viewing behavior of smart TV viewers (2018)
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- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.5, S.647-659
