Seminar Users in the Arabic Twitter Sphere

We introduce the notion of "seminar users", who are social media users engaged in propaganda in support of a political entity. We develop a framework that can identify such users with 84.4% precision and 76.1% recall. While our dataset is from the Arab region, omitting language-specific features has only a minor impact on classification performance, and thus, our approach could work for detecting seminar users in other parts of the world and in other languages. We further explored a controversial political topic to observe the prevalence and potential potency of such users. In our case study, we found that 25% of the users engaged in the topic are in fact seminar users and their tweets make nearly a third of the on-topic tweets. Moreover, they are often successful in affecting mainstream discourse with coordinated hashtag campaigns.Comment: to appear in SocInfo 201

Image Analysis Enhanced Event Detection from Geo-tagged Tweet Streams

Events detected from social media streams often include early signs of accidents, crimes or disasters. Therefore, they can be used by related parties for timely and efficient response. Although significant progress has been made on event detection from tweet streams, most existing methods have not considered the posted images in tweets, which provide richer information than the text, and potentially can be a reliable indicator of whether an event occurs or not. In this paper, we design an event detection algorithm that combines textual, statistical and image information, following an unsupervised machine learning approach. Specifically, the algorithm starts with semantic and statistical analyses to obtain a list of tweet clusters, each of which corresponds to an event candidate, and then performs image analysis to separate events from non-events---a convolutional autoencoder is trained for each cluster as an anomaly detector, where a part of the images are used as the training data and the remaining images are used as the test instances. Our experiments on multiple datasets verify that when an event occurs, the mean reconstruction errors of the training and test images are much closer, compared with the case where the candidate is a non-event cluster. Based on this finding, the algorithm rejects a candidate if the difference is larger than a threshold. Experimental results over millions of tweets demonstrate that this image analysis enhanced approach can significantly increase the precision with minimum impact on the recall.Comment: 12 pages, 4 figure

Solution-processed, Self-organized Organic Single Crystal Arrays with Controlled Crystal Orientation

A facile solution process for the fabrication of organic single crystal semiconductor devices which meets the demand for low-cost and large-area fabrication of high performance electronic devices is demonstrated. In this paper, we develop a bottom-up method which enables direct formation of organic semiconductor single crystals at selected locations with desired orientations. Here oriented growth of one-dimensional organic crystals is achieved by using self-assembly of organic molecules as the driving force to align these crystals in patterned regions. Based upon the self-organized organic single crystals, we fabricate organic field effect transistor arrays which exhibit an average field-effect mobility of 1.1 cm2V−1s−1. This method can be carried out under ambient atmosphere at room temperature, thus particularly promising for production of future plastic electronics

From computational discovery to experimental characterization of a high hole mobility organic crystal

For organic semiconductors to find ubiquitous electronics applications, the development of new materials with high mobility and air stability is critical. Despite the versatility of carbon, exploratory chemical synthesis in the vast chemical space can be hindered by synthetic and characterization difficulties. Here we show that in silico screening of novel derivatives of the dinaphtho[2,3-b:2′,3′-f]thieno[3,2-b]thiophene semiconductor with high hole mobility and air stability can lead to the discovery of a new high-performance semiconductor. On the basis of estimates from the Marcus theory of charge transfer rates, we identified a novel compound expected to demonstrate a theoretic twofold improvement in mobility over the parent molecule. Synthetic and electrical characterization of the compound is reported with single-crystal field-effect transistors, showing a remarkable saturation and linear mobility of 12.3 and 16 cm2 V−1 s−1, respectively. This is one of the very few organic semiconductors with mobility greater than 10 cm2 V−1 s−1 reported to date

Stencil Nano Lithography Based on a Nanoscale Polymer Shadow Mask: Towards Organic Nanoelectronics

A stencil lithography technique has been developed to fabricate organic-material-based electronic devices with sub-micron resolution. Suspended polymethylmethacrylate ( PMMA) membranes were used as shadow masks for defining organic channels and top electrodes. Arrays of pentacene field effect transistors (FETs) with various channel lengths from 50 mu m down to 500 nm were successfully produced from the same batch using this technique. Electrical transport measurements showed that the electrical contacts of all devices were stable and the normalized contact resistances were much lower than previously studied organic FETs. Scaling effects, originating from the bulk space charge current, were investigated by analyzing the channel-length-dependent mobility and hysteresis behaviors. This novel lithography method provides a reliable means for studying the fundamental transport properties of organic materials at the nanoscale as well as enabling potential applications requiring the fabrication of integrated organic nanoelectronic devices.open1155sciescopu