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People tweet more than 100 Million times daily, yielding a noisy, informal, but sometimes informative corpus of 140-character messages that mirrors the zeitgeist in an unprecedented manner. The performance of standard NLP tools is severely degraded on tweets. This paper addresses this issue by rebuilding the NLP pipeline beginning with part-of-speech(More)
Humans have the conscious experience of 'free will': we feel we can generate our actions, and thus affect our environment. Here we used the perceived time of intentional actions and of their sensory consequences as a means to study consciousness of action. These perceived times were attracted together in conscious awareness, so that subjects perceived(More)
Intentional action involves both a series of neural events in the motor areas of the brain, and also a distinctive conscious experience that "I" am the author of the action. This paper investigates some possible ways in which these neural and phenomenal events may be related. Recent models of motor prediction are relevant to the conscious experience of(More)
Part-of-speech information is a prerequisite in many NLP algorithms. However, Twitter text is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We present a detailed error analysis of existing taggers, motivating a series of tagger augmentations which are demonstrated to improve performance. We identify and(More)
Myofibrillar proteins assemble to form the highly ordered repetitive contractile structural unit known as a sarcomere. Studies of myogenesis in vertebrate cell culture and embryonic developmental systems have identified some of the processes involved during sarcomere formation. However, isoform changes during vertebrate muscle development and a lack of(More)
This paper is an overview of the SwatCS system submitted to SemEval-2013 Task 2A: Contextual Polarity Disambiguation. The sentiment of individual phrases within a tweet are labeled using a combination of classifiers trained on a range of lexical features. The classifiers are combined by estimating the accuracy of the classifiers on each tweet. Performance(More)
Music is categorized into subjective categories called genres. Humans have been the primary tool in attributing genre-tags to songs. Using a machine to automate this classification process is a more complex task. Machine learning excels at deciphering patterns from complex data. We aimed to apply machine learning to the task of music genre tagging using(More)
I develop and test two competing models assessing the impacts of targeted government transfers on a local incumbent's electoral performance. I take advantage of the randomized roll-out of a large-scale Conditional Cash Transfer program in the Philippines, which offers an ideal setting to test the models. Although the program was usually implemented in all(More)
The Youth Access to Alcohol (YATA) project was implemented in 2002 by the Alcohol Advisory Council of New Zealand (ALAC) in thirty communities in New Zealand, with the aim of reducing the harm experienced by young people as a result of alcohol misuse in New Zealand through reducing the supply of alcohol by adults to young people. The communities include a(More)
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