-
Zhang, C.; Zeng, D.; Li, J.; Wang, F.-Y.; Zuo, W.: Sentiment analysis of Chinese documents : from sentence to document level (2009)
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- Abstract
- User-generated content on the Web has become an extremely valuable source for mining and analyzing user opinions on any topic. Recent years have seen an increasing body of work investigating methods to recognize favorable and unfavorable sentiments toward specific subjects from online text. However, most of these efforts focus on English and there have been very few studies on sentiment analysis of Chinese content. This paper aims to address the unique challenges posed by Chinese sentiment analysis. We propose a rule-based approach including two phases: (1) determining each sentence's sentiment based on word dependency, and (2) aggregating sentences to predict the document sentiment. We report the results of an experimental study comparing our approach with three machine learning-based approaches using two sets of Chinese articles. These results illustrate the effectiveness of our proposed method and its advantages against learning-based approaches.
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2474-2487
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Hu, B.; Dong, X.; Zhang, C.; Bowman, T.D.; Ding, Y.; Milojevic, S.; Ni, C.; Yan, E.; Larivière, V.: ¬A lead-lag analysis of the topic evolution patterns for preprints and publications (2015)
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- Abstract
- This study applied LDA (latent Dirichlet allocation) and regression analysis to conduct a lead-lag analysis to identify different topic evolution patterns between preprints and papers from arXiv and the Web of Science (WoS) in astrophysics over the last 20 years (1992-2011). Fifty topics in arXiv and WoS were generated using an LDA algorithm and then regression models were used to explain 4 types of topic growth patterns. Based on the slopes of the fitted equation curves, the paper redefines the topic trends and popularity. Results show that arXiv and WoS share similar topics in a given domain, but differ in evolution trends. Topics in WoS lose their popularity much earlier and their durations of popularity are shorter than those in arXiv. This work demonstrates that open access preprints have stronger growth tendency as compared to traditional printed publications.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2643-2656
-
Li, L.; He, D.; Zhang, C.; Geng, L.; Zhang, K.: Characterizing peer-judged answer quality on academic Q&A sites : a cross-disciplinary case study on ResearchGate (2018)
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- Abstract
- Purpose Academic social (question and answer) Q&A sites are now utilised by millions of scholars and researchers for seeking and sharing discipline-specific information. However, little is known about the factors that can affect their votes on the quality of an answer, nor how the discipline might influence these factors. The paper aims to discuss this issue. Design/methodology/approach Using 1,021 answers collected over three disciplines (library and information services, history of art, and astrophysics) in ResearchGate, statistical analysis is performed to identify the characteristics of high-quality academic answers, and comparisons were made across the three disciplines. In particular, two major categories of characteristics of the answer provider and answer content were extracted and examined. Findings The results reveal that high-quality answers on academic social Q&A sites tend to possess two characteristics: first, they are provided by scholars with higher academic reputations (e.g. more followers, etc.); and second, they provide objective information (e.g. longer answer with fewer subjective opinions). However, the impact of these factors varies across disciplines, e.g., objectivity is more favourable in physics than in other disciplines. Originality/value The study is envisioned to help academic Q&A sites to select and recommend high-quality answers across different disciplines, especially in a cold-start scenario where the answer has not received enough judgements from peers.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 70(2018) no.3, S.269-287
-
Zhang, C.; Zhao, H.; Chi, X.; Ma, S.: Information organization patterns from online users in a social network (2019)
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- Abstract
- Recent years have seen the rise of user-generated con-tents (UGCs) in online social media. Diverse UGC sources and information overload are making it increasingly difficult to satisfy personalized information needs. To organize UGCs in a user-centered way, we should not only map them based on textual top-ics but also link them with users and even user communities. We propose a multi-dimensional framework to organize information by connecting UGCs, users, and user communities. First, we use a topic model to generate a topic hierarchy from UGCs. Second, an author-topic model is applied to learn user interests. Third, user communities are detected through a label propagation algo-rithm. Finally, a multi-dimensional information organization pat-tern is formulated based on similarities among the topic hierar-chies of UGCs, user interests, and user communities. The results reveal that: 1) our proposed framework can organize information rom multiple sources in a user-centered way; 2) hierarchical topic structures can provide comprehensive and in-depth topics for us-ers; and, 3) user communities are efficient in helping people to connect with others who have similar interests.
-
Wang, X.; Hong, Z.; Xu, Y.(C.); Zhang, C.; Ling, H.: Relevance judgments of mobile commercial information (2014)
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- Abstract
- In the age of mobile commerce, users receive floods of commercial messages. How do users judge the relevance of such information? Is their relevance judgment affected by contextual factors, such as location and time? How do message content and contextual factors affect users' privacy concerns? With a focus on mobile ads, we propose a research model based on theories of relevance judgment and mobile marketing research. We suggest topicality, reliability, and economic value as key content factors and location and time as key contextual factors. We found mobile relevance judgment is affected mainly by content factors, whereas privacy concerns are affected by both content and contextual factors. Moreover, topicality and economic value have a synergetic effect that makes a message more relevant. Higher topicality and location precision exacerbate privacy concerns, whereas message reliability alleviates privacy concerns caused by location precision. These findings reveal an interesting intricacy in user relevance judgment and privacy concerns and provide nuanced guidance for the design and delivery of mobile commercial information.
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.7, S.1335-1348
-
Yao, X.; Zhang, C.: Global village or virtual balkans? : evolution and performance of scientific collaboration in the information age (2020)
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- Abstract
- Scientific collaboration is essential and almost imperative in modern science. However, collaboration may be difficult to achieve because of 2 major barriers: geographic distance and social divides. It is predicted that the advancement of information communication technologies (ICTs) will bring a puzzled conclusion for collaboration in the scientific community: the "Global Village" trend with significantly increased physical distance among collaborated scientists and the "Virtual Balkans" trend with significantly increased social stratification among collaborated scientists. The results of this study reveal that the scientific community evolves towards the Global Village generally on both the geographic and social dimension, but with variations in term of collaboration patterns. The influence of such collaboration patterns on research performance (that is, productivity and impact), however, is asymmetric to each side of collaborators. When researchers from top-tier and general-tier institutions collaborate, researchers from top-tier institutions face a decrease in research productivity and impact, whereas researchers from general-tier institutions increase in research productivity and impact. Furthermore, the development of ICTs plays an important role in shaping the evolving trends and moderating effects of collaboration patterns. Our findings provide a comprehensive understanding of scientific collaboration in the geographic, social, and technological aspect.
- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.4, S.395-408
-
Xu, H.; Bu, Y.; Liu, M.; Zhang, C.; Sun, M.; Zhang, Y.; Meyer, E.; Salas, E.; Ding, Y.: Team power dynamics and team impact : new perspectives on scientific collaboration using career age as a proxy for team power (2022)
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- Abstract
- Power dynamics influence every aspect of scientific collaboration. Team power dynamics can be measured by team power level and team power hierarchy. Team power level is conceptualized as the average level of the possession of resources, expertise, or decision-making authorities of a team. Team power hierarchy represents the vertical differences of the possessions of resources in a team. In Science of Science, few studies have looked at scientific collaboration from the perspective of team power dynamics. This research examines how team power dynamics affect team impact to fill the research gap. In this research, all coauthors of one publication are treated as one team. Team power level and team power hierarchy of one team are measured by the mean and Gini index of career age of coauthors in this team. Team impact is quantified by citations of a paper authored by this team. By analyzing over 7.7 million teams from Science (e.g., Computer Science, Physics), Social Sciences (e.g., Sociology, Library & Information Science), and Arts & Humanities (e.g., Art), we find that flat team structure is associated with higher team impact, especially when teams have high team power level. These findings have been repeated in all five disciplines except Art, and are consistent in various types of teams from Computer Science including teams from industry or academia, teams with different gender groups, teams with geographical contrast, and teams with distinct size.
- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.10, S.1489-1505
-
Zhang, C.; Bu, Y.; Ding, Y.; Xu, J.: Understanding scientific collaboration : homophily, transitivity, and preferential attachment (2018)
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- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.1, S.72-86
-
Lu, C.; Bu, Y.; Wang, J.; Ding, Y.; Torvik, V.; Schnaars, M.; Zhang, C.: Examining scientific writing styles from the perspective of linguistic complexity : a cross-level moderation model (2019)
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- Source
- Journal of the Association for Information Science and Technology. 70(2019) no.5, S.462-475
-
Zhang, C.; Liu, X.; Xu, Y.(C.); Wang, Y.: Quality-structure index : a new metric to measure scientific journal influence (2011)
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- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.4, S.643-653
-
Zhang, Y.; Zhang, C.; Li, J.: Joint modeling of characters, words, and conversation contexts for microblog keyphrase extraction (2020)
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- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.5, S.553-567
-
Lu, C.; Zhang, Y.; Ahn, Y.-Y.; Ding, Y.; Zhang, C.; Ma, D.: Co-contributorship network and division of labor in individual scientific collaborations (2020)
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- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.10, S.1162-1178
-
Zhang, Y.; Zhang, C.: Enhancing keyphrase extraction from microblogs using human reading time (2021)
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- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.5, S.611-626
