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  • × author_ss:"Ding, Y."
  1. Tan, L.K.-W.; Na, J.-C.; Ding, Y.: Influence diffusion detection using the influence style (INFUSE) model (2015) 0.07 
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    Abstract
    Blogs are readily available sources of opinions and sentiments that in turn could influence the opinions of the blog readers. Previous studies have attempted to infer influence from blog features, but they have ignored the possible influence styles that describe the different ways in which influence is exerted. We propose a novel approach to analyzing bloggers' influence styles and using the influence styles as features to improve the performance of influence diffusion detection among linked bloggers. The proposed influence style (INFUSE) model describes bloggers' influence through their engagement style, persuasion style, and persona. Methods used include similarity analysis to detect the creating-sharing aspect of engagement style, subjectivity analysis to measure persuasion style, and sentiment analysis to identify persona style. We further extend the INFUSE model to detect influence diffusion among linked bloggers based on the bloggers' influence styles. The INFUSE model performed well with an average F1 score of 76% compared with the in-degree and sentiment-value baseline approaches. Previous studies have focused on the existence of influence among linked bloggers in detecting influence diffusion, but our INFUSE model is shown to provide a fine-grained description of the manner in which influence is diffused based on the bloggers' influence styles.
  2. 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) 0.06 
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    Abstract
    Publishing articles in high-impact English journals is difficult for scholars around the world, especially for non-native English-speaking scholars (NNESs), most of whom struggle with proficiency in English. To uncover the differences in English scientific writing between native English-speaking scholars (NESs) and NNESs, we collected a large-scale data set containing more than 150,000 full-text articles published in PLoS between 2006 and 2015. We divided these articles into three groups according to the ethnic backgrounds of the first and corresponding authors, obtained by Ethnea, and examined the scientific writing styles in English from a two-fold perspective of linguistic complexity: (a) syntactic complexity, including measurements of sentence length and sentence complexity; and (b) lexical complexity, including measurements of lexical diversity, lexical density, and lexical sophistication. The observations suggest marginal differences between groups in syntactical and lexical complexity.
  3. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.01 
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    Date
    22. 1.2011 13:02:21
  4. Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014) 0.01 
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    Date
    22. 8.2014 16:52:04

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