Actively open-minded thinking is key to combating fake news: A multimethod study

The fake news phenomenon has exposed the vulnerability of individuals and societies to information manipulation in social media. We conducted two studies to understand why people believe in fake news and propose a simple IT intervention method that can help in detecting disinformation. In Study 1, we designed a laboratory experiment using behavioral and neurophysiological tools to test two competing theories in the disinformation literature. Both behavioral and neurophysiological evidence support the classical reasoning account hypotheses and reject the motivated reasoning predictions, suggesting that the lack of actively open-minded thinking (AOT) is linked to the belief in fake news. An intervention method was designed (i.e., performance feedback) that reduces individuals’ overconfidence in their ability to detect fake news and encourages more analytical thinking. In Study 2, we conducted an online survey presenting participants with their performance feedback halfway through the survey. The results show that the intervention increased participants’ performance by 14%. Our study contributes to the research on fake news by providing behavioral and neurophysiological evidence in support of the classical reasoning account. It also offers a simple and practical method that increases users’ ability to detect fake news.     

Weblogs: simplifying web publishing

A weblog - blog, for short - is a Web site that uses a dated log format to publish periodical information. The updates are frequent, usually daily, according to the site owner's editorial purposes - or whims. Blogs contribute to Web content by linking and filtering evolving content in a structured way and by establishing interlinked communities - the blogosphere - connecting people through shared interests. Bloggers can link to news feeds, personal journals, and topic-specific blogs of almost every sort. Blogging systems are emerging tools that make it easier to set up a blog; to update, distribute, and archive its information; and to enhance its functionality.     

基于Ontology的信息抽取研究综述

信息抽取研究旨在为人们提供更有力的信息获取工具，以应对信息爆炸带来的严重挑战。Ontology作为领域知识的共同理解，能有效地解决现在信息抽取所面临的主要挑战——知识工程的瓶颈问题。文中详细介绍了本体的定义和建模语言，分析了现有基于本体信息抽职的几种典型方法，得出了其所存在的主要问题。     

Inferring user interest

As the World Wide Web continues to grow, people find it impossible to access even a small portion of the information generated in a day from Usenet news, e-mail, and Web postings. Automated filters help us to prioritize and access only the information in which we're interested. Because opinions differ about the importance or relevance of information, people need personalized filters. Implicit indicators captured while users browse the Web can be as predictive of interest levels as explicit ratings     

Stumbling upon news on the Internet: Effects of incidental news exposure and relative entertainment use on political engagement

Contemporary concerns that the Internet might lead to political apathy are based on suggestions that people would use the Internet for entertainment purposes rather than news consumption. However, what if someone stumbles upon news when surfing the Internet? Would this incidental news exposure online be helpful in promoting citizens’ political engagement? This study tests whether and how incidental news exposure (INE) and relative entertainment use (REU) on the Internet are associated with political participation. Drawing from US national data, results revealed a significant and positive relationship between INE and offline and online political participation while REU was negatively associated with offline and online political participation. More importantly, the role of INE in facilitating citizens’ online political participation was stronger for those who consume less entertainment online, indicating that incidental news exposure may increase existing gaps in political participation between people who prefer news and people who prefer entertainment online.     

Digital News Consumption and Copyright Intervention: Evidence from Spain Before and After the 2015 “Link Tax”

We analyze patterns of digital news consumption before and after a “link tax” was introduced in Spain. This new legislation imposed a copyright fee for showing snippets of content created by newspapers and resulted in the shutdown of Google News Spain. The Spanish copyright law is a precedent to the Copyright Directive currently submitted to the European Parliament, which is planning to impose a similar “link tax.” We offer empirical evidence that can help evaluate the impact of that sort of intervention. We analyze data tracking news consumption behavior to assess changes in audience reach and audience fragmentation. We show that the law has no discernible impact on reach, but we identify an increase in the fragmentation of news consumption.     

Personalized News Recommendation: A Review and an Experimental Investigation

Online news articles,as a new format of press releases,have sprung up on the Internet.With its convenience and recency,more and more people prefer to read news online instead of reading the paper-format press releases.However,a gigantic amount of news events might be released at a rate of hundreds,even thousands per hour.A challenging problem is how to efficiently select specific news articles from a large corpus of newly-published press releases to recommend to individual readers,where the selected news items should match the reader’s reading preference as much as possible.This issue refers to personalized news recommendation.Recently,personalized news recommendation has become a promising research direction as the Internet provides fast access to real-time information from multiple sources around the world.Existing personalized news recommendation systems strive to adapt their services to individual users by virtue of both user and news content information.A variety of techniques have been proposed to tackle personalized news recommendation,including content-based,collaborative filtering systems and hybrid versions of these two.In this paper,we provide a comprehensive investigation of existing personalized news recommenders.We discuss several essential issues underlying the problem of personalized news recommendation,and explore possible solutions for performance improvement.Further,we provide an empirical study on a collection of news articles obtained from various news websites,and evaluate the effect of different factors for personalized news recommendation.We hope our discussion and exploration would provide insights for researchers who are interested in personalized news recommendation.     

基于局部话题句群的事件相关多文档摘要研究

多文档自动文摘研究的目的是给用户提供简洁全面的文档信息并提高用户获取信息的效率。在进行局部话题确定时,通常是利用聚类分析的方法把相似的文本单元聚成一个局部话题。该文提出了一种针对新闻事件的多文档摘要生成方法,其特色在于：在提取基本新闻要素和扩展新闻要素的基础上分别形成了基本局部话题句群（BPTSG）和扩展局部话题句群（EPTSG）,这样可以在尽可能全面地覆盖多个话题的同时缩减自身的冗余。此外,文中还提出了一种基于事件时间和句子位置信息的文摘句排序方法。实验结果验证了该文所提的方法是有效的,与基于聚类的自动文摘系统相比较,该系统生成的摘要质量有显著提高。     

Fake News Identification and Classification Using DSSM and Improved Recurrent Neural Network Classifier

ABSTRACT

The widespread use of social media has enormous consequences for the society, culture and business with potentially positive and negative effects. As online social networks are increasingly used for dissemination of information, at the same they are also becoming a medium for the spread of fake news for various commercial and political purposes. Technologies such as Artificial Intelligence (AI) and Natural Language Processing (NLP) tools offer great promise for researchers to build systems, which could automatically detect fake news. However, detecting fake news is a challenging task to accomplish as it requires models to summarize the news and compare it to the actual news in order to classify it as fake. This project proposes a framework that detects and classifies fake news messages using improved Recurrent Neural Networks and Deep Structured Semantic Model. The proposed approach intuitively identifies important features associated with fake news without previous domain knowledge while achieving accuracy 99%. The performance analysis method used for the proposed system is based on accuracy, specificity and sensitivity.     

网络新闻发展中存在的问题与对策

随着网络技术的发展,人们的生活方式也产生了很大的变化,网络新闻成为人们获取信息的一种重要途径,因其信息传播速度较快而深受大家的喜爱.然而在网络新闻的发展过程中也存在一些问题,使它的真实性让人怀疑.本文提出了网络新闻发展中存在的问题及解决问题的对策,希望对网络新闻的健康发展有一定的启示.     

基于JSP技术的新闻发布系统

随着网络的飞速发展和普及,越来越多的用户习惯上网浏览新闻。网页逐渐融入人们的生活,已成为人们日常生活的一部分。另外企业通过网站可以展示产品,发布最新动态,与用户进行交流和沟通,与合作伙伴建立联系等等。该文论述的就是采用JSP Tomcat MySQL开发环境开发动态的Web网络新闻发布系统。本系统实现新闻的浏览,新闻的搜索与点评,同时还得兼顾栏目的路径信息,新闻图片信息。推荐新闻信息,新闻点击信息和新闻审核信息等。另外后台管理员可以对新闻进行添加,审核,修改和删除。     

个性化新闻推荐技术研究综述

新闻每时每刻都在发生,阅读新闻已经成为很多人的习惯。新闻媒体众多,网络媒体凭其迅捷性和便利性成为很多人的首选。网络新闻众多导致新闻过载,这就迫切需要个性化的新闻推荐系统,帮助用户快速地找到感兴趣的新闻。伴随着新闻大数据的产生和移动互联网的蓬勃发展,个性化新闻推荐迎来了新的机遇和挑战。首先介绍了个性化新闻推荐的挑战性;然后提出了个性化新闻推荐系统的基本框架,该框架包含新闻建模、用户建模、推荐引擎和用户接口四个模块,并以该框架为基础,分别综述了每个模块的研究进展,列举了现有的个性化新闻推荐系统中四个模块所采用的技术;最后总结了常用数据集、实验方法、评测指标和未来的研究方向。     

康复机器人与智能辅助系统的研究进展

我国正面临日益严重的老龄化问题和数量庞大的残疾人群,康复机器人与智能辅助系统的研究开发和应用有望为解决养老、失能辅助和康复问题提供部分技术手段.康复机器人与智能辅助系统涉及医学、信息、机械、电子、材料、力学等多个学科领域,其研究与开发也面临诸多挑战和困难,本文从“康复机器人及多种康复训练模式”、“智能辅助系统与生机电技术”、“康复与辅助相关的多模态传感与控制方法”、“外骨骼和可穿戴系统、智能假肢与人机安全性”等方面介绍和讨论康复机器人和智能辅助系统的问题和研究进展,以期为未来康复机器人和智能辅助系统的研究与开发提供些许借鉴.     

Rethinking Technology-Enhanced Physics Teacher Education: From Theory to Practice

This article discusses how modern technology, such as electronic response systems, PeerWise system, data collection and analysis tools, computer simulations, and modeling software can be used in physics methods courses to promote teacher-candidates' professional competencies and their positive attitudes about mathematics and science education. We show how modeling technology-enhanced deliberate pedagogical thinking in physics methods courses can improve teacher-candidates' subject-specific pedagogical knowledge and their positive attitudes about science learning. We also discuss potential challenges that must be addressed in order to help teacher-candidates successfully implement these pedagogies during the practicum and in their early years of teaching.     

控制访问驱动器或文件夹的一种技术

计算机普及之后，以计算机病毒、非法存取等为代表的计算机安全问题成为了信息安全的新热点。人们研制各种反病毒的工具，并采用多种有效的身份识别和访问控制机制。针对公用计算机，进行驱动器或文件夹的访问控制，保证个人信息具有保密性。提出了一种密码访问驱动器或文件夹的关键技术，采用Web、Flash与VB技术集成，实现了计算机用户密码访问驱动器或文件夹的需求。     

News recommender system: a review of recent progress,challenges, and opportunities

Nowadays, more and more news readers read news online where they have access to millions of news articles from multiple sources. In order to help users find the right and relevant content, news recommender systems (NRS) are developed to relieve the information overload problem and suggest news items that might be of interest for the news readers. In this paper, we highlight the major challenges faced by the NRS and identify the possible solutions from the state-of-the-art. Our discussion is divided into two parts. In the first part, we present an overview of the recommendation solutions, datasets, evaluation criteria beyond accuracy and recommendation platforms being used in the NRS. We also talk about two popular classes of models that have been successfully used in recent years. In the second part, we focus on the deep neural networks as solutions to build the NRS. Different from previous surveys, we study the effects of news recommendations on user behaviors and try to suggest possible remedies to mitigate those effects. By providing the state-of-the-art knowledge, this survey can help researchers and professional practitioners have a better understanding of the recent developments in news recommendation algorithms. In addition, this survey sheds light on the potential new directions.

     

Inventive Tool Use to Comprehend Big Code

Software developers often need to understand a large body of unfamiliar code with little or no documentation, no experts to consult, and little time to do it. A post appeared in January 2008 on Slashdot, a technology news Web site, asking for tools and techniques that could help. This article analyzes 301 often passionate and sometimes articulate responses to this query, including the themes and the associated tool recommendations. The most common suggestions were to use a code navigation tool, use a design recovery tool, use a debugger to step through the code, create a runtime trace, use problem-based learning, ask people for help, study the code from top down, and print out all the code. This analysis presents an intriguing snapshot of how software developers in industry go about comprehending big code.     

CASE TOOLS AS CATALYSTS FOR REENGINEERING Partial Tool Support Is Better than None

Reengineering is a vital process for reclaiming past information systems investments. This article discusses how current CASE tools can help with systems reengineering efforts and provides a listing of popular tools.