Networked Press Freedom and Social Media: Tracing Historical and Contemporary Forces in Press‐Public Relations

This paper analyzes how mainstream, online news organizations understand press autonomy in their relationships to audiences. I situate the press in terms of neo‐institutional sociology, seeing its autonomy as a distributed, field‐level phenomenon involving “boundary work” among distributed actors. I then trace press‐audience relations through two historical examples (letters to the editor and ombudsmen), showing how the press has historically both separated itself from and relied upon audiences. Examining eight news organizations' social media policies, I analyze the “inside‐out” and “outside‐in” forces through which the press distinguishes itself from audiences, concluding with a discussion of how such guidelines structure the types of control that news organizations have, or might have, as they use social network sites in their news work.     

Trust perceptions of online travel information by different content creators: Some social and legal implications

Consumers are increasingly turning to the online environment to provide information to assist them in making purchase decisions related to travel products. They often rely on travel recommendations from different sources, such as sellers, independent experts and, increasingly, other consumers. A new type of online content, user-generated content (UGC), provides a number of legal and social challenges to providers and users of that content, especially in relation to areas such as defamation, misrepresentation and social embarrassment. This paper reports research that examined the level of trustworthiness of online travel information from these different sources. The study used a survey of Australian travel consumers (n = 12,000) and results support the notion that there are differences in the level of trust for online travel information from different sources. Respondents ‘tended to agree’ that they trusted information provided by travel agents, information from commercial operators and comments made by travellers on third party websites. However, the highest level of trust was afforded to information provided on State government tourism websites. These results suggest that greater trust is placed in online travel comments when they are on a specific travel website than when they are on a more generic social networking website. However, respondents were ‘not sure’ that they trusted comments made by travellers on weblogs and on social networking sites. Some 88% of respondents that had not visited UGC websites (or were unsure if they had) indicated that they thought that UGC would be useful in the future – suggesting that they feel that any concerns they may have in relation to legal and social problems resulting from its use will be resolved.     

Effects of the News‐Finds‐Me Perception in Communication: Social Media Use Implications for News Seeking and Learning About Politics

With social media at the forefront of today's media context, citizens may perceive they don't need to actively seek news because they will be exposed to news and remain well‐informed through their peers and social networks. We label this the “news‐finds‐me perception,” and test its implications for news seeking and political knowledge: “news‐finds‐me effects.” U.S. panel‐survey data show that individuals who perceive news will find them are less likely to use traditional news sources and are less knowledgeable about politics over time. Although the news‐finds‐me perception is positively associated with news exposure on social media, this behavior doesn't facilitate political learning. These results suggest news continues to enhance political knowledge best when actively sought.     

The Shot Heard Around the World Wide Web: Who Heard What Where About Osama bin Laden's Death

This study investigated what sources were relied on to find out about Osama bin Laden's death and whether perceptions of credibility and political party affiliation influenced these media choices. The most striking difference in media reliance for bin Laden news was that whatever sources Tea Partiers relied on and thought credible were those that Democrats did not rely on or see as credible. Despite the clamor about how quickly news flows through social network sites and Twitter, only about 5% of respondents first heard about bin Laden through these sources and a slightly larger percentage spread the news via these tools. Moreover, social network sites and Twitter were the least relied on about the aftermath of bin Laden's death.     

Followee recommendation based on text analysis of micro-blogging activity

Nowadays, more and more users keep up with news through information streams coming from real-time micro-blogging activity offered by services such as Twitter. In these sites, information is shared via a followers/followees social network structure in which a follower receives all the micro-blogs from his/her followees. Recent research efforts on understanding micro-blogging as a novel form of communication and news spreading medium have identified three different categories of users in these systems: information sources, information seekers and friends. As social networks grow in the number of registered users, finding relevant and reliable users to receive interesting information becomes essential. In this paper we propose a followee recommender system based on both the analysis of the content of micro-blogs to detect users' interests and in the exploration of the topology of the network to find candidate users for recommendation. Experimental evaluation was conducted in order to determine the impact of different profiling strategies based on the text analysis of micro-blogs as well as several factors that allows the identification of users acting as good information sources. We found that user-generated content available in the network is a rich source of information for profiling users and finding like-minded people.     

How are social and mass media different in relation to the stock market? A study on topic coverage and predictive value

Although investors in financial markets have access to information from both mass media and social media, trading platforms that curate and provide this information have little to go by in terms of understanding the difference between these two types of media. This paper compares social media with mass media in the stock market, focusing on information coverage diversity and predictive value with respect to future stock absolute returns. Based on a study of nearly a million stock-related news articles from the Sina Finance news platform and 12.7 million stock-related social media messages from the popular Weibo platform in China, we find that social media covers less stocks than mass media, and this effect is amplified as the volume of media information increases. We find that there is some short-term predictive value from these sources, but they are different. Although mass media information coverage is more predictive than social media information coverage in a one-day horizon, it is the other way around in a two-to five-day horizon. These empirical results suggest that social media and mass media serve stock market investors differently. We draw connections to theories related to how crowds and experts differ and offer practical implications for the design of media-related IS systems.     

Video digital libraries: contributive and decentralised

Technology usage is changing rapidly and is becoming a more mobile, more social and more multimedia-based experience. This is especially true in the area of content creation where mobile social applications used by crowds of people are challenging traditional ways of creating and distributing content, especially for applications like news dissemination. Libraries have traditionally functioned as repositories where the information content of a society is analysed, curated, organised and stored, acting as a permanent record of what is to be remembered from a society. How can this function be achieved by present-day libraries attempting to cope with mobile, social, multimedia content who’s nature and utility of which change the type of information we wish to curate and store? This information is both dynamic and organic, posing challenges to the more fixed models of information in digital libraries. In this article we describe two digital library systems that archive video content from the sports domain, and which support user annotations and merging of diverse information sources in an integrated way. We report on analysis of the deployment of these two systems and highlight how they extend the traditional role of a (digital) library.     

Personalcasting: Tailored Broadcast News

Broadcast news sources and newspapers provide society with the vast majority of real-time information. Unfortunately, cost efficiencies and real-time pressures demand that producers, editors, and writers select and organize content for stereotypical audiences. In this article we illustrate how content understanding, user modeling, and tailored presentation generation promise personalcasts on demand. Specifically, we report on the design and implementation of a personalized version of a broadcast news understanding system, MITRE’s Broadcast News Navigator (BNN), that tracks and infers user content interests and media preferences. We report on the incorporation of Local Context Analysis to both expand the user’s original query to the most related terms in the corpus, as well as to allow the user to provide interactive feedback to enhance the relevance of selected newsstories. We describe an empirical study of the search for stories on ten topics from a video corpus. By personalizing both the selection of stories and the form in which they are delivered, we provide users with tailored broadcast news. This individual news personalization provides more fine-grained content tailoring than current personalized television program level recommenders and does not rely on externally provided program metadata.     

The Hyperlinked World: A Look at How the Interactions of News Frames and Hyperlinks Influence News Credibility and Willingness to Seek Information

Prior research has identified the influence of using hyperlinks in online information gathering. This study attempts to understand first, how hyperlinks can influence individuals' perceptions of news credibility and information‐seeking behavior. Second, the paper extends previous research by examining the interaction of hyperlinks with the content of the story. In doing so, the paper examines the influence of hyperlinks on news frames. The data for the study were collected using 2 experiments embedded in web‐based survey of participants. Findings show that hyperlinks in news stories can increase perceptions of credibility as well as information‐seeking. Results reveal the interaction of news frames in the process; hyperlinks increase participants' perception of news credibility; but only in the value‐framed condition. Implications are discussed.     

Posting,commenting, and tagging: Effects of sharing news stories on Facebook

Social networking sites such as Facebook provide new ways of sharing news stories that allow users to act as opinion leaders in their networks, encourage discussion, and potentially increase their involvement in current events. This study identifies the particular features of Facebook that facilitate the discussion of news and tests their effects on involvement and feelings of influence. Participants (N = 265) in a 3 (Broadcast level: news feed vs. wall post vs. direct message) × 3 (Elaboration: opinion vs. question vs. no comment) × 2 (Involving-friends: tag vs. no tag) between-subjects factorial experiment were randomly assigned to share a story from a news website on Facebook. Results show that user involvement in the news content depends on the social affordances of the site, particularly those that allow for audience customization and those that drive network feedback. Asking the network’s opinions and targeting specific friends led to greater involvement in the news content. Discussion through comments led to a greater sense of influence and greater involvement for those sharing the news story. These findings highlight the importance of encouraging individuals to act as sources of information in their networks to drive engagement in current events in the changing news landscape.     

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.

     

Networked Resistance: The Case of WikiLeaks

In this article, WikiLeaks is embedded within broader debates relevant to both social movement and mediation theory. First, the nature of the ties between a variety of relevant actors are assessed. Second, the networked opportunities and constraints at a discursive and material level of analysis are highlighted and finally the resistance strategies they employ towards mainstream culture are addressed. It is concluded that at the heart of information and communication resistance a dynamic dialectic can be observed between mediated opportunities for disruptions and attempts of the powers that be to close down these opportunities. Furthermore, it has to be acknowledged that reliance on mainstream actors and structures for exposure, funding or hosting contentious content comes with risks for radical activists.     

基于BLSTM-Attention神经网络模型的化工事故分类

化工事故新闻数据包含新闻内容,标题以及新闻来源等方面信息,新闻内容的文本对上下文具有较强的依赖性.为了更准确地提取文本特征并提高化工事故分类的准确性,该文提出了一种基于Attention机制的双向LSTM （BLSTM-Attention）神经网络模型对化工新闻文本进行特征提取并实现文本分类.BLSTM-Attention神经网络模型能够结合文本上下文语义信息,通过正向和反向的角度来提取事故新闻的文本特征;考虑到事故新闻中不同词对文本的贡献不大相同,加入Attention机制对不同词和句子分配不同权重.最后,将该文提出的分类方法与Naive-Bayes、CNN、RNN、BLSTM分类方法在相同的化工事故新闻数据集上进行实验对比.实验结果表明：该文提出的神经网络模型BLSTM-Attention神在化工数据集上的效果更优于其他分类方法模型.     

Some of these things are not like the others: Examining motivations and political predispositions among political Facebook activity

Political engagement via social media has evolved, and web sites including Facebook continue to be a place for individuals, especially young ones, to engage politically. Because politics on social media is diverse, it makes sense that the reasons for participating in it vary. In addition, because current events information and political news is accessible via social media, the role of attention to traditional news sources in this type of political engagement is debatable. The study takes up the opportunity to address these questions by examining young people’s attention to television, print, and online news, their engagement with four Facebook political activities, and their psychological motivations for using the website politically just prior to the 2012 U.S. Presidential election. The results suggest that the primary motivations for using Facebook politically are not universal, and indeed vary by activity. They revolve around connecting with others socially, sharing information with others, and presenting oneself to others. In addition, attention to offline and online news largely do not matter. The study moves research forward by describing the variety of psychological predispositions some Facebook users bring to their political engagement with the web site, and how these predispositions vary across different Facebook political behavior.     

Credibility of Social Network Sites for Political Information Among Politically Interested Internet Users

Scholars have confirmed that political candidates are increasingly turning to social network sites (SNS) to persuade voters to vote for them, and that these sites have become prominent sources of political information. But a fundamental question arises about the sustainability of social networks as a campaign tool: How much do users trust the information they find there? This study employed an online survey to examine the degree to which politically interested online users view SNS as credible. SNS were ranked the least credible among the nine traditional and online sources examined. Reliance on social networks proved the strongest predictor of SNS credibility.     

Echo chambers online?: Politically motivated selective exposure among Internet news users1

A review of research suggests that the desire for opinion reinforcement may play a more important role in shaping individuals’ exposure to online political information than an aversion to opinion challenge. The article tests this idea using data collected via a web‐administered behavior‐tracking study with subjects recruited from the readership of 2 partisan online news sites (N = 727). The results demonstrate that opinion‐reinforcing information promotes news story exposure while opinion‐challenging information makes exposure only marginally less likely. The influence of both factors is modest, but opinion‐reinforcing information is a more important predictor. Having decided to view a news story, evidence of an aversion to opinion challenges disappears: There is no evidence that individuals abandon news stories that contain information with which they disagree. Implications and directions for future research are discussed.     

Patterns of news dissemination through online news media: A case study in China

Along with the rapid development of online news production and consumption, information spreads rapidly among news portals through reprinting and re-posting. Understanding the dissemination process of online news has important implications for policy making, crisis management, and brand imaging. As the frequency of news reprinting between two news portals expresses the social relationship between them, the topological properties of complex networks of news portals indicate the dynamic patterns of online news dissemination. This research is the first study that examines patterns and organizational structure of online news networks based on historical data collected from more than one thousand Chinese news portals. Main findings reveal that information can spread widely and rapidly through online news portals. Specifically, some major news portals exchange information with each other frequently and they exchange information with small news portals directly, implying that hot-spot events, even they are first reported by a small news portal, can be re-posted by many major news portals in a short time and then spread over the Internet quickly. The dense connections between many major news portals ensure that the spread will not be influenced greatly by the refusal to report typical events of a small part of major news portals.     

Time,place, technology: Twitter as an information source in the Wisconsin labor protests

Recently, Twitter has become a prominent part of social protest movement communication. This study examines Twitter as a new kind of citizen journalism platform emerging at the aggregate in the context of such “crisis” situations by undertaking a case study of the use of Twitter in the 2011 Wisconsin labor protests. A corpus of more than 775,000 tweets tagged with #wiunion during the first 3 weeks of the protests provides the source of the analyses. Findings suggest that significant differences exist between users who tweet via mobile devices, and thus may be present at protests, and those who tweet from computers. Mobile users post fewer URLs overall; however, when they do, they are more likely to link to traditional news sources and to provide additional hashtags for context. Over time, all link-posting declines, as users become better able to convey first-hand information. Notably, results for most analyses significantly change when restricted to original tweets only, rather than including retweets.     

The role of social sentiment in stock markets: a view from joint effects of multiple information sources

Social sentiment reflects grassroots views regarding stock trends and has played a leading role in stock movements. Previous studies have relied predominantly on statistical models, regression models or vector-based predictive models to analyze the influence of social sentiment without considering other information sources or their intrinsic interactions. However, stock movements are in essence driven by various types of highly interrelated information sources including firm characteristics, social sentiment, and professional opinions. This paper describes the degree to which the problem arises in understanding the role of social sentiment in financial markets and proposes a novel intelligent stock analysis system to solve it. It first captures social sentiment and professional opinions from textual information in social media and financial news, respectively, and then represents the whole market information space consisting of these two information sources along with firm characteristics via tensors. Finally, a tensor-based learning algorithm is utilized to capture the interactions of these information sources on stock movements. Experiments performed on an entire year of data of China Securities Index (CSI 100) stocks demonstrate the effectiveness of the proposed intelligent system to study the role of social sentiment from the perspective of joint effects of multiple information sources compared with traditional vector-based systems.     

News sharing in social media: The effect of gratifications and prior experience

Recent events indicate that sharing news in social media has become a phenomenon of increasing social, economic and political importance because individuals can now participate in news production and diffusion in large global virtual communities. Yet, knowledge about factors influencing news sharing in social media remains limited. Drawing from the uses and gratifications (U&G) and social cognitive theories (SCT), this study explored the influences of information seeking, socializing, entertainment, status seeking and prior social media sharing experience on news sharing intention. A survey was designed and administered to 203 students in a large local university. Results from structural equation modeling (SEM) analysis revealed that respondents who were driven by gratifications of information seeking, socializing, and status seeking were more likely to share news in social media platforms. Prior experience with social media was also a significant determinant of news sharing intention. Implications and directions for future work are discussed.