منابع مشابه
Predicting election trends with Twitter: Hillary Clinton versus Donald Trump
Forecasting opinion trends from real-time social media is the long-standing goal of modern-day big-data analytics. Despite its importance, there has been no conclusive scientific evidence so far that social media activity can capture the opinion of the general population at large. Here we develop analytic tools combining statistical physics of complex networks, percolation theory, natural langu...
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متن کاملMake Deep Learning Great Again: Character-Level RNN Speech Generation in the Style of Donald Trump
A character-level recurrent neural network (RNN) is a statistical language model capable of producing text that superficially resembles a training corpus. The efficacy of these networks in mimicking Shakespeare, Linux source code, and other forms of text have already been demonstrated. In this paper, we show that character-level RNNs are capable of very believably mimicking the language of Pres...
متن کامل“ I Have the Best Classifiers ” : Identifying Speech Imitating the Style of Donald Trump
These days, people love to write comments that imitate Donald Trump’s speaking style. But inevitably, a few folks won’t get the joke. It’s tragic how these people end up getting left out of all the fun. This project is an attempt to rectify the situation. If there existed a program where you could give it a comment and it would tell you if the comment is written in Trump’s style, this would sol...
متن کاملThe Role of Temporal Amplitude Modulations in the Political Arena: Hillary Clinton vs. Donald Trump
Speech is an acoustic signal with inherent amplitude modulations in the 1-9 Hz range. Recent models of speech perception propose that this rhythmic nature of speech is central to speech recognition. Moreover, rhythmic amplitude modulations have been shown to have beneficial effects on language processing and the subjective impression listeners have of the speaker. This study investigated the ro...
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ژورنال
عنوان ژورنال: Journal of Mental Health
سال: 2017
ISSN: 0963-8237,1360-0567
DOI: 10.1080/09638237.2017.1371845