相关论文: Predicting Tomorrow's Headline using Today's Twitt…

Social networking websites allow users to create and share content. Big information cascades of post resharing can form as users of these sites reshare others' posts with their friends and followers. One of the central challenges in…

Social media platforms host discussions about a wide variety of topics that arise everyday. Making sense of all the content and organising it into categories is an arduous task. A common way to deal with this issue is relying on topic…

Comment sections below online news articles enjoy growing popularity among readers. However, the overwhelming number of comments makes it infeasible for the average news consumer to read all of them and hinders engaging discussions. Most…

In this new era of social media, social networks are becoming increasingly important sources of user-generated content on the internet. These kinds of information resources, which include a lot of people's feelings, opinions, feedback, and…

In recent years, social media has been criticized for yielding polarization. Identifying emerging disagreements and growing polarization is important for journalists to create alerts and provide more balanced coverage. While recent studies…

As technology grows faster, the news spreads through social media. In order to attract more readers and acquire additional profit, some news agencies reproduce massive news in a more appealing manner. Therefore, it is essential to…

Opinion polls have been the bridge between public opinion and politicians in elections. However, developing surveys to disclose people's feedback with respect to economic issues is limited, expensive, and time-consuming. In recent years,…

The task of predicting the publication period of text documents, such as news articles, is an important but less studied problem in the field of natural language processing. Predicting the year of a news article can be useful in various…

Over the past decade humans have experienced exponential growth in the use of online resources, in particular social media and microblogging websites such as Facebook, Twitter, YouTube and also mobile applications such as WhatsApp, Line,…

In this paper, we present computational models to predict Twitter users' attitude towards a specific brand through their personal and social characteristics. We also predict their likelihood to take different actions based on their…

Social media is a rich source of user behavior and opinions. Twitter senses nearly 500 million tweets per day from 328 million users.An appropriate machine learning pipeline over this information enables up-to-date and cost-effective data…

In addition to more personalized content feeds, some leading social media platforms give a prominent role to content that is more widely popular. On Twitter, "trending topics" identify popular topics of conversation on the platform, thereby…

The dynamics and influence of fake news on Twitter during the 2016 US presidential election remains to be clarified. Here, we use a dataset of 171 million tweets in the five months preceding the election day to identify 30 million tweets,…

In many Twitter studies, it is important to know where a tweet came from in order to use the tweet content to study regional user behavior. However, researchers using Twitter to understand user behavior often lack sufficient geo-tagged…

Slanted news coverage strongly affects public opinion. This is especially true for coverage on politics and related issues, where studies have shown that bias in the news may influence elections and other collective decisions. Due to its…

This aim of this article is to explore the potential use of Wikipedia page view data for predicting electoral results. Responding to previous critiques of work using socially generated data to predict elections, which have argued that these…

Social Networks represent one of the most important online sources to share content across a world-scale audience. In this context, predicting whether a post will have any impact in terms of engagement is of crucial importance to drive the…

In recent years, social networks have shown diversity in function and applications. People begin to use multiple online social networks simultaneously for different demands. The ability to uncover a user's latent topic and social network…

Digital traces of conversations in micro-blogging platforms and OSNs provide information about user opinion with a high degree of resolution. These information sources can be exploited to under- stand and monitor collective behaviors. In…

With the proliferation of social media over the last decade, determining people's attitude with respect to a specific topic, document, interaction or events has fueled research interest in natural language processing and introduced a new…