Visual topical analysis of Chinese and American Library and Information Science research institutions

Luo, An; Yu, Chuanming; Li, Gang

doi:10.1016/j.joi.2013.12.002

Cited by 8 publications

(6 citation statements)

References 21 publications

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“…The U-matrix is a common SOM display in which the value of each unit equals the sum of the Euclidean distances of an SOM node to all its immediate neighboring nodes normalized by the largest occurring value in the SOM grid. Due to its many advantages, the SOM technique has been widely used in many fields (An et al, 2011(An et al, , 2014Zhang et al, 2009). However, few studies utilized the SOM technique to analyze the topical evolution of microblogs, especially microblogs on public emergencies.…”

Section: Visual Analysis Of Microblogsmentioning

confidence: 99%

“…The linear initiation and batch learning algorithms are employed to train the matrix M1 since related studies (An et al, 2014) have shown that the smallest final quantization error was achieved by this combination among all of the combinations of random/linear initiation and sequential/batch learning. The background color of the SOM display was determined by the U-matrix.…”

Section: Analysis Of Topics In English Ebola Tweetsmentioning

confidence: 99%

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Topical evolution patterns and temporal trends of microblogs on public health emergencies

Luo

Lin

et al. 2018

OIR

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Purpose The purpose of this paper is to identify salient topic categories and outline their evolution patterns and temporal trends in microblogs on a public health emergency across different stages. Comparisons were also examined to reveal the similarities and differences between those patterns and trends on microblog platforms of different languages and from different nations. Design/methodology/approach A total of 459,266 microblog entries about the Ebola outbreak in West Africa in 2014 on Twitter and Weibo were collected for nine months after the inception of the outbreak. Topics were detected by the latent Dirichlet allocation model and classified into several categories. The daily tweets were analyzed with the self-organizing map technique and labeled with the most salient topics. The investigated time span was divided into three stages, and the most salient topic categories were identified for each stage. Findings In total, 14 salient topic categories were identified in microblogs about the Ebola outbreak and were summarized as increasing, decreasing, fluctuating or ephemeral types. The topical evolution patterns of microblogs and temporal trends for topic categories vary on different microblog platforms. Twitter users were keen on the dynamics of the Ebola outbreak, such as status description, secondary events and so forth, while Weibo users focused on background knowledge of Ebola and precautions. Originality/value This study revealed evolution patterns and temporal trends of microblog topics on a public health emergency. The findings can help administrators of public health emergencies and microblog communities work together to better satisfy information needs and physical demands by the public when public health emergencies are in progress.

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Section: Visual Analysis Of Microblogsmentioning

confidence: 99%

Section: Analysis Of Topics In English Ebola Tweetsmentioning

confidence: 99%

Topical evolution patterns and temporal trends of microblogs on public health emergencies

Luo

Lin

et al. 2018

OIR

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“…So it's necessary to distinct their difference at a more subtle level. Belter and Sen (2014) recommend topics as one metric for the evaluation of NOAA R&D. An et al (2014) find that early researches at the institution level in a certain research field lack of the details of the specific research topics, so they defined the salient research topics as those high-frequency controlled terms and then compared the main LIS institutions in America and China. (2011) pointed out that some high-frequency keywords are non-specific words and therefore are of limited values in the bibliometric analysis; Liu and Ma (2013) argued that the high-frequency keywords cannot be used for distinguishing knowledge content.…”

Section: Bibliometrics Analysis Of Research Institutionsmentioning

confidence: 99%

“…Research institutions are crucial to scientific innovation and the competiveness of nations (Abramo and D'Angelo 2014;An et al 2014). Yan and Sugimoto (2011) stated that the research institution is ''a stable and representative element of studying the production, diffusion and consumption of knowledge''.…”

Section: Introductionmentioning

confidence: 99%

Identifying the research focus of Library and Information Science institutions in China with institution-specific keywords

Guo

Changping

et al. 2015

Scientometrics

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In order to distinguish the research focus between different Library and Information Science (LIS) research institutions in China, we use the Keyword Activity Index (KAI) to identify their institution-specific keywords. The KAI, whose idea is borrowed from the Activity Index, measures whether an institution has alternatively comparative advantage in a particular topic according to its share in publications. In this study, a total of 65,653 papers from 19 core LIS journals in China during the period of 2000-2013 are collected. The top 8 most prolific LIS research institutions in China are selected for further investigation of the utility of KAI. Their institution-specific keywords are extracted based on the KAI values to represent their research focus and then clustered using co-word analysis; the research advantages of each institution are analyzed and compared according to these clusters. The reasons of their research advantages are analyzed based on their research function and research background.

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“…For example, An and Li (2010) proposed and employed a novel self-organizing map (SOM) display named Attribute Accumulative Matrix to identify seven clusters of salient themes in sixty LIS journals in English. An et al (2014) identified the top ten salient controlled terms by the investigated Chinese and American LIS research institutions and proposed a novel SOM display named Compound Component Plane to reveal the main contributing research institutions to the salient controlled terms in China and America. However, the contributions of the investigated research institutions to individual salient themes were unknown and the salience of each term was not differentiated.…”

Section: Detection Of Salient Themes and Related Empirical Studiesmentioning

confidence: 99%

Measuring and visualizing the contributions of Chinese and American LIS research institutions to emerging themes and salient themes

Luo

Lin

et al. 2015

Scientometrics

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Novelty and salience of the research topics are vital for the competitiveness of research institutions and the development of science and technology. In this study, two novel weighting methods were proposed to differentiate the emergence and salience of research topics. A methodology was constructed to measure and visualize the contributions of research institutions to emerging themes and salient ones. The methods were illustrated with the data of ninety Chinese and American Library and Information Science research institutions collected from the Engineering Compendex and China National Knowledge Infrastructure databases between 2001 and 2012. The contributions of the investigated research institutions to the emerging themes and salient ones were calculated and visualized with the Treemap technique. The institutions were further ranked by their contributions and categorized into four types. The findings can help research institutions evaluate novelty and salience of their research topics, discover research fronts and hotspots and promote their research development.

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Visual topical analysis of Chinese and American Library and Information Science research institutions

Cited by 8 publications

References 21 publications

Topical evolution patterns and temporal trends of microblogs on public health emergencies

Topical evolution patterns and temporal trends of microblogs on public health emergencies

Identifying the research focus of Library and Information Science institutions in China with institution-specific keywords

Measuring and visualizing the contributions of Chinese and American LIS research institutions to emerging themes and salient themes

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