From popularity prediction to ranking online news
نویسندگان
چکیده
منابع مشابه
Predicting and Evaluating the Popularity of Online News
Reading and sharing online news has become an important part of people’s entertainment lives. Therefore it would be greatly helpful if we could accurately predict the popularity of news prior to its publication for social media workers (authors, advertisers, etc.). Our goal is to predict the popularity of a news post (measured by number of shares) based on various features (see Table I.). In th...
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The use of Internet to search for information regarding a variety of topics of interest to users is still growing. The issue of how to manage and recommend that information is still an open area of research, namely concerning news recommendations. In this paper we use a recently developed approach to predict extreme and rare values of a variable to forecast the future importance of news items f...
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Popularity prediction of online news aims to predict the future popularity of news article prior to its publication estimating the number of shares, likes, and comments. Yet, popularity prediction is a challenging task due to various issues including difficulty to measure the quality of content and relevance of content to users; prediction difficulty of complex online interactions and informati...
متن کاملOnline Music Ranking Service: Ranking Mechanism Based on Popularity and Slot Effect
This paper analyzes music charts of an online music distributor. In music charts, the digital music provider displays a daily ranking of 1st ~ 100th and a weekly ranking of 1st ~ 1,000th songs on its website. And the ranking of each song is assigned based on streaming volumes and download volumes. This paper studies how the online music distributor should set its ranking policy to maximize the ...
متن کاملOnline Ranking Prediction in Non-stationary Environments
Recommender systems have to serve in online environments which can be highly non-stationary.1. Traditional recommender algorithmsmay periodically rebuild their models, but they cannot adjust to quick changes in trends caused by timely information. In our experiments, we observe that even a simple, but online trained recommender model can perform significantly better than its batch version. We i...
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ژورنال
عنوان ژورنال: Social Network Analysis and Mining
سال: 2014
ISSN: 1869-5450,1869-5469
DOI: 10.1007/s13278-014-0174-8