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Data Summarization with Social Contexts

Publications associées (42)

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Robustness, replicability and scalability in topic modelling

Orion B Penner

Approaches for estimating the similarity between individual publications are an area of long -standing interest in the scientometrics and informetrics communities. Traditional techniques have generally relied on references and other metadata, while text mi ...

ELSEVIER2022

Adapting statistical learning models online with large scale streaming data is a challenging problem. Bayesian non-parametric mixture models provide flexibility in model selection, however, their widespread use is limited by the computational overhead of e ...

2016

N-gram-Based Low-Dimensional Representation for Document Classification

Rémi Philippe Lebret, Ronan Collobert

The bag-of-words (BOW) model is the common approach for classifying documents, where words are used as feature for training a classifier. This generally involves a huge number of features. Some techniques, such as Latent Semantic Analysis (LSA) or Latent D ...

2015

Targeting HIV-related Medication Side Effects and Sentiment Using Twitter Data

Marcel Salathé

We present a descriptive analysis of Twitter data. Our study focuses on extracting the main side effects associated with HIV treatments. The crux of our work was the identification of personal tweets referring to HIV. We summarize our results in an infogra ...

2014

To improve hydro-chemical modeling and forecasting, there is a need to better understand flood-induced variability in water chemistry and the processes controlling it in watersheds. In the literature, assumptions are often made, for instance, that stream c ...

2013

A Sequential Topic Model for Mining Recurrent Activities from Long Term Video Logs

Jean-Marc Odobez, Rémi Emonet, Jagannadan Varadarajan

This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns called motifs from documents given as word×time count matrices (e.g., videos). In this model, documents are represented as a mixture of sequenti ...

Springer2013

A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets

Boi Faltings, Pearl Pu Faltings, Claudiu-Cristian Musat, Marina Boia

Emoticons are widely used to express positive or negative sentiment on Twitter. We report on a study with live users to determine whether emoticons are used to merely emphasize the sentiment of tweets, or whether they are the main elements carrying the sen ...

IEEE2013

A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets

Boi Faltings, Pearl Pu Faltings, Claudiu-Cristian Musat, Marina Boia

Ieee Computer Soc2013

Sequential Topic Models for Mining Recurrent Activities and their Relationships

Jagannadan Varadarajan

In this thesis, we address the analysis of activities from long term data logs with an emphasis on video recordings. Starting from simple words from video, we progressively build methods to infer higher level scene semantics. The main strategies used to ac ...

EPFL2012

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This paper addresses the task of mining typical behavioral patterns from small group face-to-face interactions and linking them to social-psychological group variables. Towards this goal, we define group speaking and looking cues by aggregating automatical ...

2012