منابع مشابه
Social Networks for News Media Distribution
The connectivity and availability of the Internet enables truly grassroots networks to disseminate news at the personal level. In such an environment where news abounds and anyone can publish and distribute, a method is needed to filter the overwhelming quantity of information to locate news items that are relevant to the individual. Currently search engines are the primary method to locate onl...
متن کاملTowards the social media studies of science: social media metrics, present and future
In this paper we aim at providing a general reflection around the present and future of social media metrics (or altmetrics) and how they could evolve into a new discipline focused on the study of the relationships and interactions between science and social media, in what could be seen as the social media studies of science.
متن کاملModeling and Characterizing Social Media Topics Using the Gamma Distribution
We present a novel technique to identify emerging or important topics mentioned on social media. A sudden increase in related posts can indicate an occurrence of an external event. Assuming that the sequence of posts is a homogeneous Poisson process, this sudden change can be modeled using the Gamma distribution. Our Gamma curve fitter is used to return a set of emerging topics. We demonstrate ...
متن کاملSocial Media Writing and Social Class: A Correlational Analysis of Adolescent CMC and Social Background
In a large social media corpus (2.9 million tokens), we analyze Flemish adolescents’ non-standard writing practices and look for correlations with the teenagers’ social class. Three different aspects of adolescents’ social background are included: educational track, parental profession, and home language. Since the data reveal that these parameters are highly correlated, we combine them into on...
متن کاملImproving Social Media Text Summarization by Learning Sentence Weight Distribution
Recently, encoder-decoder models are widely used in social media text summarization. However, these models sometimes select noise words in irrelevant sentences as part of a summary by error, thus declining the performance. In order to inhibit irrelevant sentences and focus on key information, we propose an effective approach by learning sentence weight distribution. In our model, we build a mul...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Social Media + Society
سال: 2015
ISSN: 2056-3051,2056-3051
DOI: 10.1177/2056305115580483