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1.
Learners may increasingly encounter conflicting expert reports. However, little is known about how they deal with this challenge. We examined how learners' familiarity with a controversial historical topic affects their epistemic judgments of conflicting expert claims and sources, the interplay of their claim and source evaluation strategies, and their meta-epistemic understanding of the legitimacy of the disagreement (absolutist, multiplist, and evaluativist perspectives). In two studies, topic familiarity increased agreement with belief-consistent expert claims and the perceived trustworthiness of the expert who presented these claims. Topic familiarity also impacted the coordination of evaluation strategies and led to greater reliance on knowledge-based validation. However, topic familiarity did not affect meta-epistemic understanding of the legitimacy of the controversy. In the second study, reading an explanation about reasons for disagreements between historians resulted in higher evaluativism. Teaching about expert disagreement may be a productive approach for promoting appreciation of the diversity of knowledge. 相似文献
2.
Erina Ogawa 《Journal of Intercultural Communication Research》2019,48(3):185-202
Identity is prominent in academia, despite it being difficult to define and measure due to its dynamic and multifaceted nature. In Japan, awareness of the make-up of Japanese youth is increasingly crucial as Japan becomes a more internationalized and ageing society. This paper examines, by identity mapping and discriminant analysis, the cultural identities of 94 Japanese youth. While strong Global identities separated the respondents with from without overseas experience, ties to National identities and Relationships were found respectively for males and females. This paper suggests that regarding the study of cultural identities, gender does matter – at least in Japan. 相似文献
3.
Kai Hu Qing Luo Kunlun Qi Siluo Yang Jin Mao Xiaokang Fu Jie Zheng Huayi Wu Ya Guo Qibing Zhu 《Information processing & management》2019,56(4):1185-1203
Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations. 相似文献
4.
Ding Xiao Yugang Ji Yitong Li Fuzhen Zhuang Chuan Shi 《Information processing & management》2018,54(6):861-873
Aspect mining, which aims to extract ad hoc aspects from online reviews and predict rating or opinion on each aspect, can satisfy the personalized needs for evaluation of specific aspect on product quality. Recently, with the increase of related research, how to effectively integrate rating and review information has become the key issue for addressing this problem. Considering that matrix factorization is an effective tool for rating prediction and topic modeling is widely used for review processing, it is a natural idea to combine matrix factorization and topic modeling for aspect mining (or called aspect rating prediction). However, this idea faces several challenges on how to address suitable sharing factors, scale mismatch, and dependency relation of rating and review information. In this paper, we propose a novel model to effectively integrate Matrix factorization and Topic modeling for Aspect rating prediction (MaToAsp). To overcome the above challenges and ensure the performance, MaToAsp employs items as the sharing factors to combine matrix factorization and topic modeling, and introduces an interpretive preference probability to eliminate scale mismatch. In the hybrid model, we establish a dependency relation from ratings to sentiment terms in phrases. The experiments on two real datasets including Chinese Dianping and English Tripadvisor prove that MaToAsp not only obtains reasonable aspect identification but also achieves the best aspect rating prediction performance, compared to recent representative baselines. 相似文献
5.
Reflected in the journal Health Psychology,various topics concerning the relationship between physical health and psychological as well as sociocultural factors,being investigated on different levels and with kinds of methods,are integrated on the platform provided by health psychology. 相似文献
6.
文章在对清代安徽方志广泛阅读的基础上,分析了舆图在清代安徽方志中的采用状况,并对方志舆图的功用、绘制人员身份及资料来源、方志舆图的变化趋势进行了考察。 相似文献
7.
《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
8.
Aurora Pons-Porrata Rafael Berlanga-Llavori José Ruiz-Shulcloper 《Information processing & management》2007
In this paper, we present a topic discovery system aimed to reveal the implicit knowledge present in news streams. This knowledge is expressed as a hierarchy of topic/subtopics, where each topic contains the set of documents that are related to it and a summary extracted from these documents. Summaries so built are useful to browse and select topics of interest from the generated hierarchies. Our proposal consists of a new incremental hierarchical clustering algorithm, which combines both partitional and agglomerative approaches, taking the main benefits from them. Finally, a new summarization method based on Testor Theory has been proposed to build the topic summaries. Experimental results in the TDT2 collection demonstrate its usefulness and effectiveness not only as a topic detection system, but also as a classification and summarization tool. 相似文献
9.
In this paper, we propose a new language model, namely, a dependency structure language model, for topic detection and tracking (TDT) to compensate for weakness of unigram and bigram language models. The dependency structure language model is based on the Chow expansion theory and the dependency parse tree generated by a linguistic parser. So, long-distance dependencies can be naturally captured by the dependency structure language model. We carried out extensive experiments to verify the proposed model on topic tracking and link detection in TDT. In both cases, the dependency structure language models perform better than strong baseline approaches. 相似文献
10.
李莉莉 《湖南广播电视大学学报》2006,(2):78-80
舞蹈是以经过提炼、组织和艺术加工的人体动作为主要表现手段,表达人们的思想感情,反映社会生活的一种艺术形式。舞蹈的编导创作是实践性的活动过程。本文结合实践从舞蹈动作、舞蹈创作构思和舞蹈构图三个方面阐述和分析了如何进行舞蹈的创编。 相似文献