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1.
《Journal of Informetrics》2022,16(4):101343
In this study, MatrixSim, a new method for detecting the evolution paths of research topics based on matrix similarity, was proposed. In the analysis of research topic evolution with the help of co-word networks, in contrast to traditional methods of topic evolution path detection, such as cosine similarity and edge similarity, MatrixSim is based on the local community structure of topic communities in co-word networks and considers the similarity of research topics in both nodes and edges, that is, words and inter-word relations. Using the library and information science field as an example, two sets of experiments were designed for topic similarity detection and subject-specific research topic evolution analysis to evaluate and verify the performance of MatrixSim in detecting the evolution paths of research topics and its validity and feasibility in research topic evolution analysis. The results confirm that MatrixSim performs well in detecting the evolution paths of research topics. It can correlate important research topics, help describe the research development process in scientific fields, reveal the internal evolutionary features of research topics, and thus discover and track the research frontiers in scientific fields. This study provides significant methodological support for researchers conducting prospective research activities. 相似文献
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《Journal of Informetrics》2023,17(3):101421
Identifying research fronts is an essential aspect of promoting scientific development. Many researchers choose their research directions and topics by analyzing their field's current research fronts. Many previous researchers have used academic papers or patents to identify research fronts; however, this is potentially outdated and reduces the prospective value of the research front detection. Considering this, this work proposes adapted indicators to conduct research front topic detection based on research grant data, which aims to identify research front topics and forecast trends using path analysis. First, research topics were identified using topic modeling, and then the mapping relations from topics to both fund projects and cross-domain categories were built. Then, research front topics were detected by multi-dimensional measurements, and the evolution of research topics was analyzed using topic evolution visualization to predict development trends. Finally, the Brillouin index was used to measure the cross-domain degree. Our method was evaluated using a dataset from the field of health informatics and was shown to be effective in research front identification. We found that the proposed adapted indicators were informative in identifying the evolutional trends in the health informatics field. In addition, research grants with higher cross-domain degrees are more likely to receive a high amount of funding. 相似文献
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Leanne K. Knobloch Liesel L. Sharabi Amy L. Delaney Samantha M. Suranne 《Communication monographs》2016,83(1):25-48
To address a key gap in theorizing and research, we consider relational uncertainty as an explanation for why individuals experiencing depressive symptoms may be reluctant to talk about sensitive issues. We report closed-ended online survey data from 126 romantic couples in which one or both partners had been professionally diagnosed with depression. Results indicated that relational uncertainty mediated the positive association between depressive symptoms and topic avoidance. Partner effects from men to women also emerged. These findings are valuable for identifying relational uncertainty as a mechanism that may explain people's unwillingness to discuss challenging topics when they are experiencing depressive symptoms. 相似文献
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《Journal of Informetrics》2022,16(2):101265
Linked topics in science and technology (LTSTs) can provide new avenues for technological innovation and are a key step in the transition from basic to applied research. This paper proposes a science and technology semantic linkage integration model for discovering LTSTs. Particularly, the integrative model fuses the term co-occurrence networks of basic and applied research, which expands the completeness of topic networks by enhancing the semantic characteristics of these networks. It is found that link prediction can further reinforce the semantic association of topic terms in networks between basic and applied topics. Simple fusion explicitly linked the topic terms, which can be used as automatic seed marking for subsequent link prediction to identify implicit linking of topic terms. Furthermore, an application to the gene-engineered vaccines field depicted that newly predicted implicit relations can effectively identify LTSTs. The results also show that implicit semantic recognition of LTSTs can be enhanced through simple fusion, while the recognition of LTST can be improved through link prediction. Therefore, the proposed model can assist experts to identify LTSTs that cannot be recognized through simple fusion. 相似文献
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《Journal of Informetrics》2014,8(1):98-110
Dynamic development is an intrinsic characteristic of research topics. To study this, this paper proposes two sets of topic attributes to examine topic dynamic characteristics: topic continuity and topic popularity. Topic continuity comprises six attributes: steady, concentrating, diluting, sporadic, transforming, and emerging topics; topic popularity comprises three attributes: rising, declining, and fluctuating topics. These attributes are applied to a data set on library and information science publications during the past 11 years (2001–2011). Results show that topics on “web information retrieval”, “citation and bibliometrics”, “system and technology”, and “health science” have the highest average popularity; topics on “h-index”, “online communities”, “data preservation”, “social media”, and “web analysis” are increasingly becoming popular in library and information science. 相似文献
7.
Anthony Bigot Claude Chrisment Taoufiq Dkaki Gilles Hubert Josiane Mothe 《Information Retrieval》2011,14(6):617-648
To evaluate Information Retrieval Systems on their effectiveness, evaluation programs such as TREC offer a rigorous methodology
as well as benchmark collections. Whatever the evaluation collection used, effectiveness is generally considered globally,
averaging the results over a set of information needs. As a result, the variability of system performance is hidden as the
similarities and differences from one system to another are averaged. Moreover, the topics on which a given system succeeds
or fails are left unknown. In this paper we propose an approach based on data analysis methods (correspondence analysis and
clustering) to discover correlations between systems and to find trends in topic/system correlations. We show that it is possible
to cluster topics and systems according to system performance on these topics, some system clusters being better on some topics.
Finally, we propose a new method to consider complementary systems as based on their performances which can be applied for
example in the case of repeated queries. We consider the system profile based on the similarity of the set of TREC topics
on which systems achieve similar levels of performance. We show that this method is effective when using the TREC ad hoc collection. 相似文献
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Emerging research topic detection can benefit the research foundations and policy-makers. With the long-term and recent interest in detecting emerging research topics, various approaches are proposed in the literature. Though, there is still a lack of well-established linkages between the clear conceptual definition of emerging research topics and the proposed indicators for operationalization. This work follows the definition by Wang (2018), and several machine learning models are together used to detect and foresight the emerging research topics. Finally, experimental results on gene editing dataset discover three emerging research topics, which make clear that it is feasible to identify emerging research topics with our framework. 相似文献
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《The Journal of Academic Librarianship》2019,45(3):278-287
Research topic studies have gained popularity in many disciplines, including library and information science (LIS). However, the lack of representation of library science and librarianship in literature indicates a research bias due to the preset methodology parameters, which are commonly based on impact factor scores in the Journal Citation Report of Thomson Reuters. In research, the authors utilize an improved selection criterion of journals and author-supplied keyword clustering and analysis technique to study the most recent ten years of LIS journal publications. This article presents a clear picture of popular research topics in seminal literature to help practicing librarians and library science scholars gain a better understanding and considerable prediction on the research trends in the LIS field. 相似文献
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Research topics and research communities are not disconnected from each other: communities and topics are interwoven and co-evolving. Yet, scientometric evaluations of topics and communities have been conducted independently and synchronically, with researchers often relying on homogeneous unit of analysis, such as authors, journals, institutions, or topics. Therefore, new methods are warranted that examine the dynamic relationship between topics and communities. This paper examines how research topics are mixed and matched in evolving research communities by using a hybrid approach which integrates both topic identification and community detection techniques. Using a data set on information retrieval (IR) publications, two layers of enriched information are constructed and contrasted: one is the communities detected through the topology of coauthorship network and the other is the topics of the communities detected through the topic model. We find evidence to support the assumption that IR communities and topics are interwoven and co-evolving, and topics can be used to understand the dynamics of community structures. We recommend the use of the hybrid approach to study the dynamic interactions of topics and communities. 相似文献
12.
Brandi N. Frisby Kerry Byrnes Daniel H. Mansson Melanie Booth-Butterfield Meagan K. Birmingham 《Communication Studies》2013,64(3):241-257
Relationships are increasingly impacted by military involvement, necessitating a deeper understanding of communication within these couples. This study examined perceptions of everyday talk, topic avoidance, and stress of participants romantically involved with (a) a military partner (n = 118) or (b) a non-military partner (n = 94). Couple types avoided similar topics, but non-military partners avoided these topics more frequently than military partners. Both couple types engaged in everyday talk, but military partners found this communicative exchange to be more important. Non-military partners experienced greater stress than military partners, and communication was predictive of the stress experienced. The results of this study highlight similarities and differences in romantic couples and reveal areas in which relationship education can address these communicative nuances of military couples. 相似文献
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[目的/意义] 针对当前非正式信息交流主题演化研究在分析层次和测度指标两方面存在的局限,提出一种具有通用性的演化分析方法,从微观和中观层面探究主题演化特征与规律。[方法/过程] 引入会话分析理论,以新浪微博和知乎为例,通过对主题和主题簇运行过程进行分析,从会话内容和讨论方式两个维度揭示非正式信息交流演化特征与规律。同时,设计主题持续性计算判定方法,丰富主题演化的衡量标准。[结果/结论] 主题演化分析结果显示新浪微博和知乎意见群体的发文主题存在明显偏重,且表明了意见群体参与社会焦点事件讨论中观点的主要切入角度;主题簇演化分析发现了新浪微博意见群体在一定范围内发散探索多元主题、知乎意见群体始终关注聚焦核心主题的讨论特点。两个社交媒体中意见群体在会话内容和讨论方式方面的区别,喻示了新浪微博和知乎在网络环境的非正式信息交流中主要承担的角色差异。 相似文献
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T. S. STOINSKI M. T. ALLEN M. A. BLOOMSMITH D. L. FORTHMAN T. L. MAPLE 《Curator: The Museum Journal》2002,45(2):129-143
Modern zoos are committed to environmental education and thus have a mandate to inform the public about biodiversity and conservation. Historically, zoos have avoided complex topics like biodiversity loss from overpopulation and overconsumption in their educational materials, for fear of being offensive or creating a sense of hopelessness. To measure visitor attitudes towards educating about such topics and to help determine effective presentation techniques, we assessed people's knowledge of and attitudes towards the commercial hunting and consumption of wildlife in West and Central Africa (the bushmeat crisis) and examined how the use of different types of images affected these variables. Zoo visitors were exposed to one of six series of photographs, each accompanied by the same text. Photos in three of the series contained explicit, disturbing images of dead animals. The other three series presented benign images related to the bushmeat crisis (i.e., logging, changes in hunting practices). While 83 percnt of visitors had never heard of the bushmeat trade, 98 percent felt zoos should be educating about the topic. Ninety‐seven percent felt the disturbing images were appropriate for zoo visitors except for children under the age of 12. While people spent significantly more time looking at the disturbing images, this did not lead to increases in knowledge (factual or conservation‐related) on the topic. However, visitors who saw the disturbing images were significantly more likely to report being influenced by the images. While the type of image did not affect the frequency of conservation‐related behaviors, significantly more people engaged in a conservation‐related behavior when an opportunity was provided on‐site rather than off‐site. The results demonstrate that the public believes zoos should educate about bushmeat, and that realistic images influence people's perception of an issue. However, visitors' lack of knowledge gains, even when disturbing images are used, suggests that a static display of text with photographs may not be the most effective method for educating about complex issues like bushmeat. Finally, the results show that zoos should provide on‐site opportunities for people to turn their conservation interests into action. 相似文献
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《Communication monographs》2012,79(4):275-295
There is consistent evidence that individuals tend to be dissatisfied with their relationships if they report that topics are frequently avoided in those relationships. The extant literature contains two plausible general explanations for such findings: perceptual processes (e.g., the perceptions that the relational partner avoids are unrelated to the partner's actual avoidance but adversely influence relational satisfaction) and interpersonal processes (e.g., one individual's topic avoidance diminishes the counterpart's satisfaction because the counterpart accurately detects that avoidance). The current study compared the utility of these two explanations with data gathered from two separate samples, one including 100 heterosexual dating couples and the other including 114 parent-child dyads. Findings indicated that both perceptual processes and interpersonal processes help account for the association between topic avoidance and dissatisfaction. For example, the interpersonal explanation was consistent with evidence that boyfriends, girlfriends, and parents (but not children) all had perceptions of their counterpart's topic avoidance that were more accurate than would be expected by chance, and that those perceptions of avoidance were, in turn, associated with dissatisfaction. Despite such evidence for interpersonal factors, the effect sizes associated with perceptual processes were, in general, significantly stronger than those associated with interpersonal processes. The relative salience of the perceptual processes has important practical implications, supporting theoretical arguments that there are likely circumstances when topic avoidance can help maintain a cohesive relationship. 相似文献
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The purpose of this study is to find a theoretically grounded, practically applicable and useful granularity level of an algorithmically constructed publication-level classification of research publications (ACPLC). The level addressed is the level of research topics. The methodology we propose uses synthesis papers and their reference articles to construct a baseline classification. A dataset of about 31 million publications, and their mutual citations relations, is used to obtain several ACPLCs of different granularity. Each ACPLC is compared to the baseline classification and the best performing ACPLC is identified. The results of two case studies show that the topics of the cases are closely associated with different classes of the identified ACPLC, and that these classes tend to treat only one topic. Further, the class size variation is moderate, and only a small proportion of the publications belong to very small classes. For these reasons, we conclude that the proposed methodology is suitable to determine the topic granularity level of an ACPLC and that the ACPLC identified by this methodology is useful for bibliometric analyses. 相似文献
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While past research has shown that learning outcomes can be influenced by the amount of effort students invest during the learning process, there has been little research into this question for scenarios where people use search engines to learn. In fact, learning-related tasks represent a significant fraction of the time users spend using Web search, so methods for evaluating and optimizing search engines to maximize learning are likely to have broad impact. Thus, we introduce and evaluate a retrieval algorithm designed to maximize educational utility for a vocabulary learning task, in which users learn a set of important keywords for a given topic by reading representative documents on diverse aspects of the topic. Using a crowdsourced pilot study, we compare the learning outcomes of users across four conditions corresponding to rankings that optimize for different levels of keyword density. We find that adding keyword density to the retrieval objective gave significant learning gains on some topics, with higher levels of keyword density generally corresponding to more time spent reading per word, and stronger learning gains per word read. We conclude that our approach to optimizing search ranking for educational utility leads to retrieved document sets that ultimately may result in more efficient learning of important concepts. 相似文献
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结合2008-2009年河北省医学情报研究所查新咨询室所完成的河北省中医科研课题查新工作,分析中医科研选题中存在的问题,阐明中医科研选题原则,揭示中医科研的选题方法和发展方向,为中医科研人员选题提供参考。 相似文献
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《Journal of Informetrics》2019,13(2):695-707
Twitter accounts have already been used in many scientometric studies, but the meaningfulness of the data for societal impact measurements in research evaluation has been questioned. Earlier research focused on social media counts and neglected the interactive nature of the data. We explore a new network approach based on Twitter data in which we compare author keywords to hashtags as indicators of topics. We analyze the topics of tweeted publications and compare them with the topics of all publications (tweeted and not tweeted). Our exploratory study is based on a comprehensive publication set of climate change research. We are interested in whether Twitter data are able to reveal topics of public discussions which can be separated from research-focused topics. We find that the most tweeted topics regarding climate change research focus on the consequences of climate change for humans. Twitter users are interested in climate change publications which forecast effects of a changing climate on the environment and to adaptation, mitigation and management issues rather than in the methodology of climate-change research and causes of climate change. Our results indicate that publications using scientific jargon are less likely to be tweeted than publications using more general keywords. Twitter networks seem to be able to visualize public discussions about specific topics. 相似文献
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中国大陆使用者研究现状——十大核心期刊研究主题分布的例证 总被引：2，自引：0，他引：2
首先,分析中国大陆地区十大图书馆学和情报学期刊2002年7月至2005年6月计三年刊载文年6月计三年刊载文章主题,以了解中国大陆地区使用者和信息行为的研究现状。研究发现,“图书馆自动化、网络化”是当前中国大陆图书馆学、情报学领域的重点研究方向,并已累积丰硕成果;“中国图书馆事业”、“图书馆工作者”等主题也是学者关注的重点;而关于信息行为或使用者的研究相对缺乏。其次,将上述分析结果与台湾类似研究进行比较,并对中国大陆忽视使用者研究的现状提出分析。最后,作者希望藉由本文之分析,发掘中国信息和知识传播研究的长短处,并针对未来研究方向提出建议。 相似文献