Sources: Encyclopedia of Social Movement Media
نویسندگان
چکیده
منابع مشابه
How Noisy Social Media Text, How Diffrnt Social Media Sources?
While various claims have been made about text in social media text being noisy, there has never been a systematic study to investigate just how linguistically noisy or otherwise it is over a range of social media sources. We explore this question empirically over popular social media text types, in the form of YouTube comments, Twitter posts, web user forum posts, blog posts and Wikipedia, whi...
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Social media provide a rich source of author-identified text that can be used for personality profiling. However, differences in length and number of entries, syntax, abbreviations, spelling and grammar errors, and topics can affect type and difficulty of preprocessing to extract appropriate text, accuracy of training, time period sampling for training texts, and rate of degradation of accuracy...
متن کاملUndergraduates' Use of Social Media as Information Sources
Social media have become increasingly popular among different user groups. Although used for social purposes, some social media platforms (e.g., Wikipedia) have been emerging as important information sources. Focusing on undergraduate students, a survey was conducted to investigate the following: (1) which social media platforms are used as information sources, (2) what are the main reasons for...
متن کاملSocial Media Participation in an Activist Movement for Racial Equality
From the Arab Spring to the Occupy Movement, social media has been instrumental in driving and supporting socio-political movements throughout the world. In this paper, we present one of the first social media investigations of an activist movement around racial discrimination and police violence, known as "Black Lives Matter". Considering Twitter as a sensor for the broader community's percept...
متن کاملPredicting Stock Price Movement Using Social Media Analysis
In this project, we aim to predict stock prices by using machine learning techniques on data from StockTwits, a social media platform for investors. We demonstrate the results, and compare the prediction error, of several classification and regression techniques using aggregated StockTwits messages as a source of input.
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ژورنال
عنوان ژورنال: Reference & User Services Quarterly
سال: 2011
ISSN: 1094-9054
DOI: 10.5860/rusq.51n2.197.2