ABSTRACT Social media platforms allow users to share their messages with everyone else. In microblogs, e.g., Twitter, people mostly report on what they did, they talk about current activities, and mention things they plan to do in the near future. In this paper, we propose the task of activity prediction, that is, trying to establish a set of activities that are likely to become popular at a later time. We perform a small-scale initial experiment, in which we try to predict popular activities for the coming evening using Dutch Twitter data. Our experiment shows the feasibility and challenges of the task, with a simple method resulting in human-readable activities. This exploration also identifies several issues (e.g., temporal phrases and a...
Hashtags are widely used in Twitter to define a shared context for events or topics. In this paper, ...
Effective forecasting of future prevalent topics plays an important role in social network business ...
The advent of the era of Big Data has allowed many researchers to dig into various socio-technical s...
Social media platforms allow users to share their messages with ev-eryone else. In microblogs, e.g.,...
We discuss an approach for predicting microscopic (individual) and macroscopic (collective) user beh...
International audienceForecasting keyword activities in social networking sites has been the subject...
Abstract: A current trend for online social networks is to turn mobile. Mobile social networks direc...
This paper reports on our participation in the Data Mining track of the WISE 2012 Challenge. The cha...
Early prediction of popularity is crucial for recommendation of planned events such as concerts, con...
This dissertation is devoted to a social-media-mining problem named the activity-prediction problem....
We predict the popularity of short messages called tweets created in the micro-blogging site known a...
The data generated from social media is very large, while the use of data from social media has not ...
Purpose ‐ Social media provide an impressive amount of data about users and their interactions, ther...
Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Envir...
This paper develops a probabilistic framework that can model and predict group activity over time on...
Hashtags are widely used in Twitter to define a shared context for events or topics. In this paper, ...
Effective forecasting of future prevalent topics plays an important role in social network business ...
The advent of the era of Big Data has allowed many researchers to dig into various socio-technical s...
Social media platforms allow users to share their messages with ev-eryone else. In microblogs, e.g.,...
We discuss an approach for predicting microscopic (individual) and macroscopic (collective) user beh...
International audienceForecasting keyword activities in social networking sites has been the subject...
Abstract: A current trend for online social networks is to turn mobile. Mobile social networks direc...
This paper reports on our participation in the Data Mining track of the WISE 2012 Challenge. The cha...
Early prediction of popularity is crucial for recommendation of planned events such as concerts, con...
This dissertation is devoted to a social-media-mining problem named the activity-prediction problem....
We predict the popularity of short messages called tweets created in the micro-blogging site known a...
The data generated from social media is very large, while the use of data from social media has not ...
Purpose ‐ Social media provide an impressive amount of data about users and their interactions, ther...
Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Envir...
This paper develops a probabilistic framework that can model and predict group activity over time on...
Hashtags are widely used in Twitter to define a shared context for events or topics. In this paper, ...
Effective forecasting of future prevalent topics plays an important role in social network business ...
The advent of the era of Big Data has allowed many researchers to dig into various socio-technical s...