Wu, Shu (Institute of Automation, Chinese Academy of Sciences) | Liu, Qiang (Institute of Automation, Chinese Academy of Sciences) | Liu, Yong (Institute of Automation, Chinese Academy of Sciences) | Wang, Liang (Institute of Automation, Chinese Academy of Sciences) | Tan, Tieniu (Institute of Automation, Chinese Academy of Sciences)
With the growing online social media, rumors are spread fast and viewed by more and more people on the Internet. Rumors bring significant harm to daily life and public security. It is crucial to evaluate the credibility of information and detect the rumors on social media automatically. In this work, we establish a Network Information Credibility Evaluation (NICE) platform, which collects a database of rumors that have been verified on Sina Weibo and automatically evaluates the information generated by users on social media but has not been verified. Users can use a query to search related information. If the according information appears in our database, users can identify it is a rumor immediately. Otherwise, NICE will show users with real-time results crawled automatically from social media and can calculate credibility of a specific result with our algorithm. Our algorithm learns dynamic representations for information on social media based on behavior information, dynamic information, user information and comment information. Then, we use an ordinary logistic regression to classify information into rumors and non-rumors. Based on our algorithm, NICE system achieves satisfactory performance on evaluating information credibility and detecting rumors on social media.
Given the wide spread of web-based tools and social news media services which are facilitating grassroots journalism, there is a growing interest in selecting credible news content among a huge number of articles. Currently, most of social news services rely on reader votes to select articles for their front pages. However, the fundamental problem is that users’ votes often stand for popularity rather than credibility. In this paper, we propose a system to address this problem using a weighted voting system. Specifically, we trace thousands of users and their votes, differentiating them depending on how credible the articles voted for are. We then calculate each user’s voting credibility and use it as the user’s voting weight in our system. The results indicate that our method performs better in selecting credible news articles than other methods replying on a “one person, one vote” system. The results suggest feasible solutions to problems in social news media concerning media credibility.
Even in those cases in which your audience thinks that everything's clear, they still might not be on the same page (like when you're talking with a peer and realize that you've each walked away from a meeting with different conclusions). Instead, say: "Let's do a quick review of the key takeaways to make sure I articulated it clearly." While this might be something that's appropriate for life and death situations, for most leaders this isn't the sort of phrase you should be using too frequently. Although it seems like it sets the bar high, the reality is that it'll likely encourage mediocrity. Think about it: If people are afraid to make mistakes, do you think they'll be willing to experiment to see if they can make something better, or do you think they'll stay safely within the bounds of what they know?
And that work comes with some serious homework, said Dan Berkovitz, a former Senate investigator. There needs to be a thorough understanding of the facts surrounding the investigation, he said, which requires getting all of the appropriate documentation and interviewing all people with relevant knowledge. And good investigations take time, he said. Announcing the start of an investigation and scheduling a hearing on it weeks later "raises eyebrows."
Opposition leaders in the Democratic Republic of Congo are concerned about the credibility of the upcoming presidential election. They're worried electronic voting machines, which are being used for the first time in the country, will be manipulated to rig the result. The technology was created by a South Korean company which built similar machines for elections in Argentina last year. But the devices were then rejected because of security issues that made them vulnerable to hackers.