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1.
《Information processing & management》2022,59(2):102843
Emerging topic detection has attracted considerable attention in recent times. While various detection approaches have been proposed in this field, designing a method for accurately detecting emerging topics remains challenging. This paper introduces the perspective of knowledge ecology to the detection of emerging topics and utilizes author-keywords to represent research topics. More precisely, we first improve the novelty metric and recalculate emergence capabilities based on the “ecostate” and “ecorole” attributes of ecological niches. Then, we take the perspective that keywords are analogous to living bodies and map them to the knowledge ecosystem to construct an emerging topics detection method based on ecological niches (ETDEN). Finally, we conduct in-depth comparative experiments to verify the effectiveness and feasibility of ETDEN using data extracted from scientific literature in the ACM Digital Library database. The results demonstrate that the improved novelty indicator helps to differentiate the novelty values of keywords in the same interval. More importantly, ETDEN performs significantly better performance on three terms: the emergence time point and the growth rate of pre-and post-emergence. 相似文献
2.
【目的/意义】识别信息隐私研究领域的热点主题,梳理主题演化路径。【方法/过程】针对主题识别语义杂乱
等问题,提出时序关联与结构表征视角下的主题演化分析方法。首先利用LDA（Latent Dirichlet Allocation）模型识
别多时间窗口下的文献主题,进一步运用共词分析绘制语义更为独立的主题凝聚子群。在此基础上,从时序关联
维度计算相邻窗口下主题间的相似度,梳理演化路径;从结构表征维度,设计主题新颖度、中心性、影响力等计量指
标,探寻信息隐私前沿和热点主题的演化变迁。【结果/结论】实证分析结果表明,本文方法可以深度挖掘信息隐私
领域研究主题,从宏微观两个维度全面梳理主题的演化路径。研究有利于探测信息隐私研究的前沿。【创新/局限】
综合运用LDA主题模型与共词分析方法绘制主题凝聚子群,从时序演化和结构表征两个维度探寻主题演化路径。
未来研究中有待于引入多种数据源以对比主题差异,有待于引入多元组术语改善主题识别效果。 相似文献
3.
In this paper, a new novelty detection approach based on the identification of sentence level information patterns is proposed. First, “novelty” is redefined based on the proposed information patterns, and several different types of information patterns are given corresponding to different types of users’ information needs. Second, a thorough analysis of sentence level information patterns is elaborated using data from the TREC novelty tracks, including sentence lengths, named entities (NEs), and sentence level opinion patterns. Finally, a unified information-pattern-based approach to novelty detection (ip-BAND) is presented for both specific NE topics and more general topics. Experiments on novelty detection on data from the TREC 2002, 2003 and 2004 novelty tracks show that the proposed approach significantly improves the performance of novelty detection in terms of precision at top ranks. Future research directions are suggested. 相似文献
4.
《Information processing & management》2020,57(2):102077
Information needs motivate human information behavior. Knowledge of information needs is critical for user-centered information behavior research and system design. In consumer health information behavior research, there is a lack of understanding of how consumer health information needs (CHIN) is measured in empirical studies. This study is a systematic review of empirical quantitative studies on CHIN, with a focus on how CHIN is defined and operationalized. A search of six academic databases and citation-track of relevant articles identified a total of 216 relevant articles. These articles were analyzed using the qualitative content analysis method. We found that few included articles explicitly defined either CHIN or information needs in general. When definitions were given, they were from a cognitive perspective and largely ignored the multidimensionality of the concept. Consistent with this cognitive-centered conceptualization, CHIN was operationalized primarily as information topics, with some articles also measuring several additional attributes, including level of importance, fulfilment, amount of information needed, and frequency of needs. These findings suggest that CHIN is undertheorized. To address this gap, future studies should attend to social and emotional dimensions of CHIN, such as motivations, goals, activities, and emotions. Further, more research is needed to understand how CHIN is related to consumer health information seeking behavior and to the social and environmental context in which the needs arise. 相似文献
5.
《Information processing & management》2023,60(1):103146
The wide spread of fake news and its negative impacts on society has attracted a lot of attention to fake news detection. In existing fake news detection methods, particular attention has been paid to the credibility of the users sharing the news on social media, and the news sources based on their level of participation in fake news dissemination. However, these methods have ignored the important role of news topical perspectives (like political viewpoint) in users'/sources' decisions to share/publish the news. These decisions are associated with the viewpoints shared by the echo-chamber that the users belong to, i.e., users' Socio-Cognitive (SC) biases, and the news sources' partisan bias. Therefore, the credibility of users and news sources are varied in different topics according to the mentioned biases; which are completely ignored in current fake news detection studies. In this paper, we propose a Multi-View Co-Attention Network (MVCAN) that jointly models the latent topic-specific credibility of users and news sources for fake news detection. The key idea is to represent news articles, users, and news sources in a way that the topical viewpoints of news articles, SC biases of users which determines the users' viewpoints in sharing news, and the partisan bias of news sources are encoded as vectors. Then a novel variant of the Multi-Head Co-Attention (MHCA) mechanism is proposed to encode the joint interaction from different views, including news-source and news-user to implicitly model the credibility of users and the news sources based on their interaction in real and fake news spreading on the news topic. We conduct extensive experiments on two public datasets. The results show that MVCAN significantly outperforms other state-of-the-art methods and outperforms the best baselines by 3% on average in terms of F1 and Accuracy. 相似文献
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7.
《Information processing & management》2022,59(6):103110
The research on studying exploration-exploitation behavior in topic choice has consistently been the focus of a great deal of attention. In this study, we propose five novel research strategies under exploration and exploitation based on the general but significant features of topics, and present a series of metrics to quantify and identify these strategies. We analyze the relationship between scientists’ research performance (i.e., productivity and impact) and their preference for different strategies, and examine the evolution of their preference in scientific careers through comprehensive statistical analysis. We employ a MAG dataset as our data source, and select about 30 million scientists from the computer science filed and their publications as our analysis objects. Our empirical analysis shows that productive and impactful scientists tend to follow academic frontiers, study diverse topics, explore emerging topics and combinatorial innovation, but exploit mature topics less often. We also figure out the potential reasons for the phenomenon. In addition, we find that successful scientists prefer to execute exploratory research strategies from the beginning of their career, and young scientists seem to be more creative. Our research may help researchers deeply understand topic selection behavior, and therefore provide enlightenment for training scientists and give advice for funding allocation as well as research and development policy formulation. 相似文献
8.
我国图书馆知识服务研究热点述评 总被引：1，自引：0，他引：1
为反映我国图书馆知识服务领域的研究进展与热点内容,本文采用定量与定性相结合的方法,对1998-2008年我国图书馆知识服务领域的期刊论文进行了统计和梳理,归纳分析了目前图书馆知识服务的研究热点,并指出我国的图书馆知识服务要进一步深化基础理论研究,拓宽研究视角、重视理论研究与应用研究的协调发展,采取科学多样的研究方法。 相似文献
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10.
《International Journal of Information Management》2016,36(3):451-475
ContextNowadays the concept of knowledge mapping has attracted increased attention from scientists in a variety of academic disciplines and professional practice areas. Among the most important attributes of a knowledge map is its ability to increase communication and share common practices across an entire organisation. However, despite being a promising area for research, the knowledge maps community lacks a widespread understanding of the current state of the art.ObjectiveThe objective of this article is to explore the world of knowledge mapping by reviewing and analysing the current state of research and providing an overview of knowledge mapping’s concepts, benefits, techniques, classifications and methodologies, which are precisely reviewed, and their features are highlighted. In addition, we offer directions for future research.MethodBased on the systematic literature review method this study collects, synthesises, and analyses numerous articles on a variety of topics closely related to a knowledge map published from January 2000 to December 2013 on six electronic databases by following a pre-defined review protocol. The articles have been retrieved through a combination of automatic and manual search, hence extensive quantitative and qualitative results of the research are provided.ResultsFrom the review study, we identified 132 articles addressing knowledge maps that have been reviewed in order to extract relevant information on a set of research questions. We found a generally increasing level of activity during this 5-year period. We noted that while existing research covers a large number of studies on some disciplines, such as systems and tools development, it contains very few studies on other disciplines, such as knowledge maps adoption. To aid this situation, we offer directions for future research.ConclusionsThe results demonstrated that a knowledge map is an imperative strategy for increasing organisations’ effectiveness. In addition, there is a need for more knowledge maps research. 相似文献
11.
《Research Policy》2023,52(6):104766
We analyze whether journal editors exhibit home bias in their acceptance decisions towards researchers affiliated with institutions in the editor's home country. Our results show that the fraction of articles accepted by authors affiliated with European civil-law countries increase by 33 % when an editor from the same country serves in the journal. We analyze various possible reasons for this phenomenon and conclude that a likely explanation for the bias is that, in civil-law countries, there is greater emphasis on individuals' solidarity with institutions. We also document that this bias extends to the European Union as a whole. Importantly, articles that are potentially subject to editorial home bias have 10 % lower impact than similar articles. Overall, the findings are consistent with the idea that cultural values potentially foster editorial-biased behavior and hinder scientific progress. 相似文献
12.
科技成果查新的质量控制 总被引：2，自引：1，他引：1
李玲 《科技成果管理与研究》2009,(1):23-25,32
本文从科技成果的内涵分析入手,提出了一种应用于科技成果查新的科技成果分类方法,通过对各类科技成果查新的重点、方法以及文献资源进行针对性的选择,使科技成果查新的质量得到有效地控制。作者还从宏观管理的角度提出了提高科技成果查新质量的对策及措施。 相似文献
13.
《Research Policy》2019,48(7):1771-1780
Science’s main norms prescribe scientists to use citations as acknowledgements of cognitive content irrespective of geographical location. Previous studies, however, suggested that there is a considerable geographical bias in scientific citations. We argue that this geographical bias does not, in itself, falsify the notion that citations reflect acknowledgement of cognitive content, because cognitively related knowledge may be geographically concentrated as well. We analyse the role of organizational, regional and national co-location on citation likelihood for 5.5 million article pairs, and find that the geographical bias in citations is weak once cognitive relatedness is accounted for. Furthermore, we find that the effect of co-location on citation likelihood is strongest at the organizational level, weaker at the regional level, and weakest at the national level. In addition, we show that geographical co-location particularly increases the citation likelihood between two papers when knowledge relatedness between articles is low, suggesting that interdisciplinary research benefits most from co-location. Finally, we find that, when knowledge relatedness is high, the effect of geographical co-location on citation likelihood is non-existent. We discuss the implications regarding policies aimed to discourage strategic citations and to foster interdisciplinary research. 相似文献
14.
《Research Policy》2019,48(9):103822
This paper builds new theory and provides supporting evidence to contain the Not-Invented-Here Syndrome (NIHS) – a persistent decision-making error arising from an attitude-based bias against external knowledge. Conceptually, we draw on the 4i framework of organizational learning to develop a novel process perspective on NIHS. This allows us not only to unpack how and where NIHS impedes organizational learning, but also to identify the key requirements for effective NIHS countermeasures. Importantly, countermeasures fall into two categories: those that seek to change the negative attitude directly (direct NIHS countermeasures) and those that seek to attenuate the behavioral impact of negative attitudes without addressing the attitudes as such (indirect NIHS countermeasures). While the evidence base on direct NIHS countermeasures has grown over the last decade, indirect NIHS countermeasures have received little research attention. To address this gap, we adopt a mixed methods research design composed of two complementary empirical studies – the first qualitative and the second quantitative. Study 1 explores the prevalence of distinct NIHS countermeasures in collaborative R&D practice. Based on 32 interviews and three focus group meetings with R&D employees, we find that a broad array of primarily direct NIHS countermeasures is employed in R&D practice. Study 2 addresses the scarcity of scholarly and managerial insights on indirect NIHS countermeasures by testing the effectiveness of perspective taking as a debiasing technique to contain negative attitudes at the level of the individual. Based on quantitative survey data from 565 global R&D projects, it provides empirical evidence not only for the prevalence and negative effects of NIHS on project success as mediated by external knowledge absorption, but also for the effectiveness of perspective taking as an exemplary indirect NIHS countermeasure. 相似文献
15.
Emerging topic detection is a vital research area for researchers and scholars interested in searching for and tracking new research trends and topics. The current methods of text mining and data mining used for this purpose focus only on the frequency of which subjects are mentioned, and ignore the novelty of the subject which is also critical, but beyond the scope of a frequency study. This work tackles this inadequacy to propose a new set of indices for emerging topic detection. They are the novelty index (NI) and the published volume index (PVI). This new set of indices is created based on time, volume, frequency and represents a resolution to provide a more precise set of prediction indices. They are then utilized to determine the detection point (DP) of new emerging topics. Following the detection point, the intersection decides the worth of a new topic. The algorithms presented in this paper can be used to decide the novelty and life span of an emerging topic in a specific field. The entire comprehensive collection of the ACM Digital Library is examined in the experiments. The application of the NI and PVI gives a promising indication of emerging topics in conferences and journals. 相似文献
16.
《Information processing & management》2019,56(3):584-608
“We the Media” networks are real time and open, and such networks lack a gatekeeper system. As netizens’ comments on emergency events are disseminated, negative public opinion topics and confrontations concerning those events also spread widely on “We the Media” networks. Gradually, this phenomenon has attracted scholarly attention, and all social circles attach importance to the phenomenon as well. In existing topic detection studies, a topic is mainly defined as an "event" from the perspective of news-media information flow, but in the “We the Media” era, there are often many different views or topics surrounding a specific public opinion event. In this paper, a study on the detection of public opinion topics in “We the Media” networks is presented, starting with the characteristics of the elements found in public opinions on “We the Media” networks; such public opinions are multidimensional, multilayered and possess multiple attributes. By categorizing the elements’ attributes using social psychology and system science categories as references, we build a multidimensional network model oriented toward the topology of public opinions on “We the Media” networks. Based on the real process by which multiple topics concerning the same event are generated and disseminated, we designed a topic detection algorithm that works on these multidimensional public opinion networks. As a case study, the “Explosion in Tianjin Port on August 12, 2015″ accident was selected to conduct empirical analyses on the algorithm's effectiveness. The theoretical and empirical research findings of this paper are summarized along the following three aspects. 1. The multidimensional network model can be used to effectively characterize the communication characteristics of multiple topics on “We the Media” networks, and it provided the modeling ideas for the present paper and for other related studies on “We the Media” public opinion networks. 2. Using the multidimensional topic detection algorithm, 70% of the public opinion topics concerning the case study event were effectively detected, which shows that the algorithm is effective at detecting topics from the information flow on “We the Media” networks. 3. By defining the psychological scores of single and paired Chinese keywords in public opinion information, the topic detection algorithm can also be used to judge the sentiment tendencies of each topic, which can facilitate a timely understanding of public opinion and reveal negative topics under discussion on “We the Media” networks. 相似文献
17.
Adopting an agnotological perspective, this article extends the critical literature on APIs (application programing interfaces) by systematically showing that social media APIs are largely blind to acts of disconnectivity such as unfriending and unliking. We do this through analysis of the traces of social media usage that are not accessible through APIs as gleaned from the technical documentation published for developers by 12 major SNSs. Our findings make two main contributions. First, we show for the first time that APIs offer virtually no access to data about disconnectivity. Second, we show that APIs offer a very limited historical perspective, particularly regarding disconnectivity. However, for types of users that might spend money on advertising, far more historical and disconnectivity-oriented information is accessible through the API. This has practical consequences for research and contributes to an agnotology of social media that sheds critical light on the advertiser-friendly atmosphere of connectivity that social media try to create. 相似文献
18.
The advancement in mobile technology has enabled the application of the mobile wallet or m-wallet as an innovative payment method to substitute the traditional functions of the physical wallet. However, because of pro-innovation bias, scholars have a focus on the adoption of technology and very little attention has been given to the resistance of innovation, especially in the m-wallet context. This study addressed this absence by examining the inhibitors of m-wallet innovation adoption through the lens of innovation resistance theory (IRT). By applying a sophisticated two-staged structural equation modeling-artificial neural network (SEM-ANN) approach, we successfully extended the IRT by integrating socio-demographics and perceived novelty. The study has unveiled the noncompensatory and nonlinear relationships between the predictors and m-wallet resistance. Significant predictors from SEM analysis were taken as the ANN model’s input neurons. According to the normalized importance obtained from the multilayer perceptrons of the feed-forward-back-propagation ANN algorithm, we found significant effects of education, income, usage barrier, risk barrier, value barrier, tradition barrier, and perceived novelty on m-wallet innovation resistance. The ANN model can predict m-wallet innovation resistance with an accuracy of 76.4 %. We also discussed several new and useful theoretical and practical implications for reducing m-wallet innovation resistance among consumers. 相似文献
19.
《Information processing & management》2020,57(2):102142
With the information explosion of news articles, personalized news recommendation has become important for users to quickly find news that they are interested in. Existing methods on news recommendation mainly include collaborative filtering methods which rely on direct user-item interactions and content based methods which characterize the content of user reading history. Although these methods have achieved good performances, they still suffer from data sparse problem, since most of them fail to extensively exploit high-order structure information (similar users tend to read similar news articles) in news recommendation systems. In this paper, we propose to build a heterogeneous graph to explicitly model the interactions among users, news and latent topics. The incorporated topic information would help indicate a user’s interest and alleviate the sparsity of user-item interactions. Then we take advantage of graph neural networks to learn user and news representations that encode high-order structure information by propagating embeddings over the graph. The learned user embeddings with complete historic user clicks capture the users’ long-term interests. We also consider a user’s short-term interest using the recent reading history with an attention based LSTM model. Experimental results on real-world datasets show that our proposed model significantly outperforms state-of-the-art methods on news recommendation. 相似文献
20.
There is no doubt that scientific discoveries have always brought changes to society. New technologies help solve social problems such as transportation and education, while research brings benefits such as curing diseases and improving food production. Despite the impacts caused by science and society on each other, this relationship is rarely studied and they are often seen as different universes. Previous literature focuses only on a single domain, detecting social demands or research fronts for example, without ever crossing the results for new insights. In this work, we create a system that is able to assess the relationship between social and scholar data using the topics discussed in social networks and research topics. We use the articles as science sensors and humans as social sensors via social networks. Topic modeling algorithms are used to extract and label social subjects and research themes and then topic correlation metrics are used to create links between them if they have a significant relationship. The proposed system is based on topic modeling, labeling and correlation from heterogeneous sources, so it can be used in a variety of scenarios. We make an evaluation of the approach using a large-scale Twitter corpus combined with a PubMed article corpus. In both of them, we work with data of the Zika epidemic in the world, as this scenario provides topics and discussions on both domains. Our work was capable of discovering links between various topics of different domains, which suggests that some of the relationships can be automatically inferred by the sensors. Results can open new opportunities for forecasting social behavior, assess community interest in a scientific subject or directing research to the population welfare. 相似文献