BlogNewsRank: Finding and Ranking Frequent News Topics Using Social Media Factors
نویسندگان
چکیده
منابع مشابه
Finding Correlative Associations among News Topics
A method for finding real-world associations between news topics (as distinguished from apparent associations caused by the constant size of the newsp aper) is described. This is important for studying society interests. Introduction.* Text mining is a new area of text processing that can be defined as discovery of interesting facts and new world knowledge from large text collections [2]. Its m...
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 کاملCryptocurrency Price Prediction Using News and Social Media Sentiment
This project analyzes the ability of news and social media data to predict price fluctuations for three cryptocurrencies: bitcoin, litecoin and ethereum. Traditional supervised learning algorithms were utilized for text-based sentiment classification, but with a twist. Daily news and social media data was labeled based on actual price changes one day in the future for each coin, rather than on ...
متن کاملRanking for Social Semantic Media
This diploma thesis is devoted to the ranking of results returned by search engines. We present a State of the Art which covers the ranking for various datatypes, including the Web, XML, RDF, and folksonomies. For every datatype the calculation of a popularity score as well as the computing of a content score is presented. For most datatypes we also discuss the relevance of two objects to each ...
متن کاملDiscovering Health Topics in Social Media Using Topic Models
By aggregating self-reported health statuses across millions of users, we seek to characterize the variety of health information discussed in Twitter. We describe a topic modeling framework for discovering health topics in Twitter, a social media website. This is an exploratory approach with the goal of understanding what health topics are commonly discussed in social media. This paper describe...
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: JOIV : International Journal on Informatics Visualization
سال: 2018
ISSN: 2549-9904,2549-9610
DOI: 10.30630/joiv.2.3.134