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Computer-mediated communication is driving fundamental changes in the nature of written language. We investigate these changes by statistical analysis of a dataset comprising 107 million Twitter messages (authored by 2.7 million unique user…
Social media datasets are essential for research on disinformation, influence operations, social sensing, hate speech detection, cyberbullying, and other significant topics. However, access to these datasets is often restricted due to costs…
Social Internet content plays an increasingly critical role in many domains, including public health, disaster management, and politics. However, its utility is limited by missing geographic information; for example, fewer than 1.6% of…
Censuses around the world are key sources of data to guide government investments and public policies. However, these sources are very expensive to obtain and are collected relatively infrequently. Over the last decade, there has been…
Large Language Models are being used in conversational agents that simulate human conversations and generate social studies data. While concerns about the models' biases have been raised and discussed in the literature, much about the data…
We demonstrate how language can improve geolocation: the task of predicting the location where an image was taken. Here we study explicit knowledge from human-written guidebooks that describe the salient and class-discriminative visual…
Online social networks are known to be demographically biased. Currently there are questions about what degree of representativity of the physical population they have, and how population biases impact user-generated content. In this paper…
Large language models are increasingly used to represent human opinions, values, or beliefs, and their steerability towards these ideals is an active area of research. Existing work focuses predominantly on aligning marginal response…
Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to…
We propose a novel crowd counting approach that leverages abundantly available unlabeled crowd imagery in a learning-to-rank framework. To induce a ranking of cropped images , we use the observation that any sub-image of a crowded scene…
Public conversations on Twitter comprise many pertinent topics including disasters, protests, politics, propaganda, sports, climate change, epidemics/pandemic outbreaks, etc., that can have both regional and global aspects. Spatial…
Analyzing the geographic movement of humans, animals, and other phenomena is a growing field of research. This research has benefited urban planning, logistics, animal migration understanding, and much more. Typically, the movement is…
The wide use of social media sites and other digital technologies have resulted in an unprecedented availability of digital data that are being used to study human behavior across research domains. Although unsolicited opinions and…
The interest in demographic information retrieval based on text data has increased in the research community because applications have shown success in different sectors such as security, marketing, heath-care, and others. Recognition and…
The "crowd" has become a very important geospatial data provider. Subsumed under the term Volunteered Geographic Information (VGI), non-expert users have been providing a wealth of quantitative geospatial data online. With spatial reasoning…
Modeling relations between languages can offer understanding of language characteristics and uncover similarities and differences between languages. Automated methods applied to large textual corpora can be seen as opportunities for novel…
Modelling and forecasting real-life human behaviour using online social media is an active endeavour of interest in politics, government, academia, and industry. Since its creation in 2006, Twitter has been proposed as a potential…
Social media users share billions of items per year, only a small fraction of which is geotagged. We present a data- driven approach for identifying non-geotagged content items that can be associated with a hyper-local geographic area by…
Research from a variety of fields including psychology and linguistics have found correlations and patterns in personal attributes and behavior, but efforts to understand the broader heterogeneity in human behavior have not yet integrated…
Twitter is a well-known microblogging social site where users express their views and opinions in real-time. As a result, tweets tend to contain valuable information. With the advancements of deep learning in the domain of natural language…