The massive spread of false information on social media has become a global risk, implicitly influencing public opinion and threatening social/political development. False information detection (FID) has thus become a surging research topic in recent years. As a promising and rapidly developing research field, we find that much effort has been paid to new research problems and approaches of FID. Therefore, it is necessary to give a comprehensive review of the new research trends of FID. We first give a brief review of the literature history of FID, based on which we present several new research challenges and techniques of it, including early detection, detection by multimodal data fusion, and explanatory detection. We further investigate the extraction and usage of various crowd intelligence in FID, which paves a promising way to tackle FID challenges. Finally, we give our views on the open issues and future research directions of FID, such as model adaptivity/generality to new events, embracing of novel machine learning models, aggregation of crowd wisdom, adversarial attack and defense in detection models, and so on.

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BackgroundThe commercial potential of social media is utilized by tobacco manufacturers and vendors for tobacco promotion online. However, the prevalence and promotional strategies of pro-tobacco content in social media are still not widely understood.ObjectiveThe goal of this study was to reveal what is presented by the tobacco industry, and how it promotes itself, on social media sites.MethodsThe top 70 popular cigarette brands are divided into two groups according to their retail prices: group H (brands with high retail prices) and group L (brands with low retail prices). Three comprehensive searches were conducted on Facebook, Wikipedia, and YouTube respectively using the top 70 popular cigarette brands as keywords. We identified tobacco-related content including history and culture, product features, health warnings, home page of cigarette brands, and Web-based tobacco shops. Furthermore, we examined the promotional strategies utilized in social media.ResultsAccording to the data collected from March 3, 2014 to March 10, 2014, 43 of the 70 representative cigarette brands had created 238 Facebook fan pages, 46 cigarette brands were identified in Wikipedia, and there were over 120,000 pro-tobacco videos on YouTube, associated with 61 cigarette brands. The main content presented on the three social media websites differs significantly. Wikipedia focuses on history and culture (67%, 32/48; P<.001). Facebook mainly covers history and culture (37%, 16/43; P<.001) and major products (35%, 15/43), while YouTube focuses on the features of major tobacco products (79%, 48/61; P=.04) and information about Web-based shops (49%, 30/61; P=.004). Concerning the content presented by groups H and L, there is no significant difference between the two groups. With regard to the promotional strategies used, sales promotions exist extensively in social media. Sales promotion is more prevalent on YouTube than on the other two sites (64%, 39/61 vs 35%, 15/43; P=.004). Generally, the sale promotions of higher-cost brands in social media are more prevalent than those of lower-cost brands (55%, 16/29 vs 7%, 1/14; P<.001 for Facebook; 78%, 28/36 vs 44%, 11/25; P=.005 for YouTube).ConclusionsThe prevalence of cigarette brands in social media allows more pro-tobacco information to be accessed by online users. This dilemma indicates that corresponding regulations should be established to prevent tobacco promotion in social media.

International audienceThe Internet of Things (IoT) represents the future technology trend of sensing, computing, and communication. Under the Wisdom Web of Things (W2T) vision, the next-generation Internet will promote harmonious interaction among humans, computers, and things. Current research on IoT is primarily conducted from the perspective of identifying, connecting, and managing objects. In this paper, however, we attempt to enhance the IoT with intelligence and awareness under the W2T vision. By exploring the various interactions between humans and the IoT, we extract the "embedded" intelligence about individual, environment, and society, which can augment existing IoT systems with user, ambient, and social awareness. The characteristics, major applications, research issues, the reference architecture, as well as our ongoing efforts to embedded intelligence are also presented and discussed

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