673 research outputs found
A Probabilistic Model for Malicious User and Rumor Detection on Social Media
Rumor detection in recent years has emerged as an important research topic, as fake news on social media now has more significant impacts on people\u27s lives, especially during complex and controversial events. Most existing rumor detection techniques, however, only provide shallow analyses of users who propagate rumors. In this paper, we propose a probabilistic model that describes user maliciousness with a two-sided perception of rumors and true stories. We model not only the behavior of retweeting rumors, but also the intention. We propose learning algorithms for discovering latent attributes and detecting rumors based on such attributes, supposedly more effectively when the stories involve retweets with mixed intentions. Using real-world rumor datasets, we show that our approach can outperform existing methods in detecting rumors, especially for more confusing stories. We also show that our approach can capture malicious users more effectively
Mining urban perceptions from social media data
This vision paper summaries the methods of using social media data (SMD) to measure urban perceptions. We highlight two major types of data sources (i.e., texts and imagery) and two corresponding techniques (i.e., natural language processing and computer vision). Recognizing the data quality issues of SMD, we propose three criteria for improving the reliability of SMD-based studies. In addition, integrating multi-source data is a promising approach to mitigating the data quality problems
Electrical transport across metal/two-dimensional carbon junctions: Edge versus side contacts
Metal/two-dimensional carbon junctions are characterized by using a nanoprobe
in an ultrahigh vacuum environment. Significant differences were found in bias
voltage (V) dependence of differential conductance (dI/dV) between edge- and
side-contact; the former exhibits a clear linear relationship (i.e., dI/dV
\propto V), whereas the latter is characterized by a nonlinear dependence,
dI/dV \propto V3/2. Theoretical calculations confirm the experimental results,
which are due to the robust two-dimensional nature of the carbon materials
under study. Our work demonstrates the importance of contact geometry in
graphene-based electronic devices
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