Recently, Peterson et al. provided evidence of the benefits of using probabilistic soft labels generated from crowd annotations for training a computer vision model, showing that using such labels maximizes performance of the models over unseen data. …
Identifying deceptive online reviews is a challenging tasks for Natural Language Processing (NLP). Collecting corpora for the task is difficult, because normally it is not possible to know whether reviews are genuine. A common workaround involves …
Prior research has shown that geolocation can be substantially improved by including user network information. While effective, it suffers from the curse of dimensionality, since networks are usually represented as sparse adjacency matrices of …
Geolocation, predicting the location of a post based on text and other information, has a huge potential for several social media applications. Typically, the problem is modeled as either multi-class classification or regression. In the first case, …
User reviews provide a significant source of information for companies to understand their market and audience. In order to discover broad trends in this source, researchers have typically used topic models such as Latent Dirichlet Allocation (LDA). …
Geolocating social media posts relies on the assumption that language carries sufficient geographic information. However, locations are usually given as continuous latitude/longitude tuples, so we first need to define discrete geographic regions …
Several linguistic studies have shown the prevalence of various lexical and grammatical patterns in texts authored by a person of a particular gender, but models for part-of-speech tagging and dependency parsing have still not adapted to account for …
Dialects are one of the main drivers of language variation, a major challenge for natural language processing tools. In most languages, dialects exist along a continuum, and are commonly discretized by combining the extent of several preselected …
The analysis of crowdsourced annotations in natural language processing is concerned with identifying (1) gold standard labels, (2) annotator accuracies and biases, and (3) item difficulties and error patterns. Traditionally, majority voting was used …
Newspapers need to attract readers with headlines, anticipating their readers’ preferences. These preferences rely on topical, structural, and lexical factors. We model each of these factors in a multi-task GRU network to predict headline popularity. …