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1.
互联网一般被看做是继电视之后的“第四媒体”，从已有的媒体结构与功能来看，“第四媒体”这种沿袭的说法有些不妥。作为传播媒体意义上的互联网，在本质上与其前辈截然不同。因此，本更倾向于把互联网看做一种媒体综合平台。若要把其归结为某一代媒体，似乎把其看做新一代媒体更为确切。 相似文献
2.
变旧闻为新闻，有三种方法：
一、以新近发生的事实为由头，把它与过去发生的同类事实链接起来
变的要点是，新闻由头的时间要素应遵循“最近点”原理。“最近点”即所选择的时间要素应尽可能是距离报道时间最近的，最好是“昨天”或“今天”发生的，如果不是则最好点明具体发生时间。新闻由头非常忌讳时间上的模糊性，如“改革开放以来”，“年初以来”等等抽象的时间概念，时间久就不成其为新闻由头。 相似文献
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高校图书馆读者活动的常态化、多元化、特色化,是将“闲暇时间优化”与“第三空间营造”有机结合的桥梁.图书馆作为“校园第三空间”,具有的多重功能包括：学习延伸功能、技能培训功能、素质教育功能、人际交流功能、休闲娱乐功能和才艺展示功能等六大方面. 相似文献
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搞新闻的人都知道,消息写作在处理时间要素时应遵循“最近点”原理。“最近点”即消息所选择的时间要素,应尽可能是距离报道时间最近的。 在新闻报道中,如果消息中的时间要素违背“最近点”原理,则是旧闻,而不是新闻、那么,怎样应用“最近点”原理处理时间要素呢？笔者结合工作实践、总结归纳出以下几种： 跟踪新闻事件的发展。 一般来说,重大活动和突发事件的发生时间就是“最近点”。记者要竭力捕捉这个无需重新寻找的“最近点”,快采快写快发稿,在消息导语中写下“今天”和“昨天”。对于那些不断出现新情况的爆炸性新闻,记者… 相似文献
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面对不断加速的社会情境,时间异化已成为当代人的普遍感知,时间的稀缺性问题也愈发受到社会各界的关注。本文基于时间社会学视角,以钉钉App中的“已读”功能为案例,通过参与式观察与半结构式访谈,探讨“已读”技术背后资本的时间政治实践以及实践过程中劳动者的时间感知体验。研究发现,资本会借用“已读”的监控、联结、提速作用,对劳动者的休闲时间进行序时重置、再同步化以及效率复刻,致使休闲时间发生异化,包括属性上的异己化以及感知体验上的“去时间化”,这被体验为时间剥夺、时间抽离以及时间恐慌。在此过程中,劳动者会摸索出一套捍卫自由时间的“潜隐剧本”,但这些策略只是基于妥协基础上的行为应对,劳动者依旧在时间争夺战中处于弱势地位。此外,本文还指出了“工作/休闲”时间异化程度的差异性,旨在为“时间异化”批判理论的优化提供参考性意见。 相似文献
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时间观念与人类社会进步的脚步始终如影随形,从循环时间观到线性时间观,乃至现代社会的钟表时间观和新时空观等,都可以看到时间观念对社会进步的影响。“大众传媒时间”是当今占据统治地位的时间观念,休闲是一个贯穿始终却又具有时代特色的人类活动,本文从时间观念考察“大众传媒时间”对人类实现休闲理想的影响。 相似文献
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本文从“自由时间”管理案例入手,阐述了图书馆传统时间管理的弊端,提出了图书馆实施“自由时间”管理的几点做法,进而重点论述了图书馆“自由时间”管理的意义。 相似文献
8.
近年来的“科幻文艺片”指称涉及类型片的“现代主义策略”问题,它往往处于类型电影研究的边界,而借助吉尔·德勒兹关于“现代电影”的根本性思考可以进一步揭示“策略”背后的美学依据。战后兴起的现代电影曾借用科幻片的样式,试图在类型框架内开展“时间-影像”的电影实验,其关键是将题材内容与电影经验中的“时间”问题化,由自在的变成自为的。所谓“科幻文艺片”正是延续了这一美学策略与传统,通过对“纯视听情境”“回忆-影像”与“时间绵延”进行科幻式的想象与呈现,将叙事结构、风格样式、影像形式与题材内容统一在时间问题中,为科幻类型电影与艺术电影的融合创造了可能。 相似文献
9.
据笔者所知,不少读者是比较喜欢读文摘报刊或有些报纸的文摘版(栏)的。然而令人不安的是,越来越多的文摘稿常常只抓住一个“新”字,忽略了一个“实”字。因此有人说:“文摘”只能看做专载国内稿件的“参考消息”。例如湖南《文艺生活》1986年第8期刊载的“当代传奇”《陈毅与被处决的市长》,纯属胡编乱造,可是这篇稿件不仅几家专登文摘的报纸迅速 相似文献
10.
据笔者所知,不少读者是比较喜欢读文摘报刊或有些报纸的文摘版(栏)的。然而令人不安的是,越来越多的文摘稿常常只抓住一个“新”字,忽略了一个“实”字。因此有人说:“文摘”只能看做专载国内稿件的“参考消息”。例如湖南《文艺生活》1986年第8期刊载的“当代传奇”《陈毅与被处决的市长》,纯属胡编乱造,可是这篇稿件不仅几家专登文摘的报纸迅速 相似文献
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The pervasive use of multiple technological tools to engage with media and political content (i.e., TV sets, laptops, tablets, smartphones, etc.) has deeply altered the way citizens around the world consume information and discuss public affair issues. Many are using 2, or even several “screens” at the same time to do so, a phenomenon known as second or dual screening.
The goal of this article is twofold. First, it introduces a set of novel studies published as a special section devoted to second screening. Second, based on nationally representative original survey data collected in twenty societies (N = 22.033), the study depicts a snapshot of second screening habits for news and politics around the world. Findings reveal that young people tend to second screen more than older counterparts. Similarly, there are also differences in political behaviors between groups of high and low frequency second screen users. More intensive users tend to politically express themselves in social media, and participate more often in offline political activities. On the other hand, results indicate little or no differences between these two groups in terms of their voting behavior. 相似文献
12.
Word embeddings and convolutional neural networks (CNN) have attracted extensive attention in various classification tasks for Twitter, e.g. sentiment classification. However, the effect of the configuration used to generate the word embeddings on the classification performance has not been studied in the existing literature. In this paper, using a Twitter election classification task that aims to detect election-related tweets, we investigate the impact of the background dataset used to train the embedding models, as well as the parameters of the word embedding training process, namely the context window size, the dimensionality and the number of negative samples, on the attained classification performance. By comparing the classification results of word embedding models that have been trained using different background corpora (e.g. Wikipedia articles and Twitter microposts), we show that the background data should align with the Twitter classification dataset both in data type and time period to achieve significantly better performance compared to baselines such as SVM with TF-IDF. Moreover, by evaluating the results of word embedding models trained using various context window sizes and dimensionalities, we find that large context window and dimension sizes are preferable to improve the performance. However, the number of negative samples parameter does not significantly affect the performance of the CNN classifiers. Our experimental results also show that choosing the correct word embedding model for use with CNN leads to statistically significant improvements over various baselines such as random, SVM with TF-IDF and SVM with word embeddings. Finally, for out-of-vocabulary (OOV) words that are not available in the learned word embedding models, we show that a simple OOV strategy to randomly initialise the OOV words without any prior knowledge is sufficient to attain a good classification performance among the current OOV strategies (e.g. a random initialisation using statistics of the pre-trained word embedding models). 相似文献
13.
Gatekeepers usually control news information. However, recent technological advancements might require rethinking previous gatekeeping hierarchies. Aggregation algorithms currently filter and present news information to millions of American Internet users daily. A content analysis demonstrates significant differences between health news content retrieved from Web sites that aggregate their articles from many sources (e.g., Google News), and those that focus on providing news from a limited number of sources (e.g., CNN.com). Explanations for these content differences are discussed, as are implications concerning health information seeking and Internet news consumption. 相似文献
14.
In retrieving medical free text, users are often interested in answers pertinent to certain scenarios that correspond to common
tasks performed in medical practice, e.g., treatment or diagnosis of a disease. A major challenge in handling such queries is that scenario terms in the query (e.g., treatment) are often too general to match specialized terms in relevant documents (e.g., chemotherapy). In this paper, we propose a knowledge-based query expansion method that exploits the UMLS knowledge source to append the
original query with additional terms that are specifically relevant to the query's scenario(s). We compared the proposed method
with traditional statistical expansion that expands terms which are statistically correlated but not necessarily scenario
specific. Our study on two standard testbeds shows that the knowledge-based method, by providing scenario-specific expansion,
yields notable improvements over the statistical method in terms of average precision-recall. On the OHSUMED testbed, for
example, the improvement is more than 5% averaging over all scenario-specific queries studied and about 10% for queries that
mention certain scenarios, such as treatment of a disease and differential diagnosis of a symptom/disease.
相似文献
| Wesley W. ChuEmail: |
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Objectives:
The research investigated the extent to which students, residents, and faculty members in Canadian medical faculties use mobile devices, such as smartphones (e.g., iPhone, Android, Blackberry) and tablet computers (e.g., iPad), to answer clinical questions and find medical information. The results of this study will inform how health libraries can effectively support mobile technology and collections.Methods:
An electronic survey was distributed by medical librarians at four Canadian universities to medical students, residents, and faculty members via departmental email discussion lists, personal contacts, and relevant websites. It investigated the types of information sought, facilitators to mobile device use in medical information seeking, barriers to access, support needs, familiarity with institutionally licensed resources, and most frequently used resources.Results:
The survey of 1,210 respondents indicated widespread use of smartphones and tablets in clinical settings in 4 Canadian universities. Third- and fourth-year undergraduate students (i.e., those in their clinical clerkships) and medical residents, compared to other graduate students and faculty, used their mobile devices more often, used them for a broader range of activities, and purchased more resources for their devices.Conclusions:
Technological and intellectual barriers do not seem to prevent medical trainees and faculty from regularly using mobile devices for their medical information searches; however, barriers to access and lack of awareness might keep them from using reliable, library-licensed resources.Implications:
Libraries should focus on providing access to a smaller number of highly used mobile resources instead of a huge collection until library-licensed mobile resources have streamlined authentication processes. 相似文献16.
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Exploiting Hierarchy in Text Categorization 总被引：4，自引：3，他引：1
With the recent dramatic increase in electronic access to documents, text categorization—the task of assigning topics to a given document—has moved to the center of the information sciences and knowledge management. This article uses the structure that is present in the semantic space of topics in order to improve performance in text categorization: according to their meaning, topics can be grouped together into meta-topics, e.g., gold, silver, and copper are all metals. The proposed architecture matches the hierarchical structure of the topic space, as opposed to a flat model that ignores the structure. It accommodates both single and multiple topic assignments for each document. Its probabilistic interpretation allows its predictions to be combined in a principled way with information from other sources. The first level of the architecture predicts the probabilities of the meta-topic groups. This allows the individual models for each topic on the second level to focus on finer discriminations within the group. Evaluating the performance of a two-level implementation on the Reuters-22173 testbed of newswire articles shows the most significant improvement for rare classes. 相似文献