Search Results for author:
Found 10 papers, 5 papers with code
Generalized Word Shift Graphs: A Method for Visualizing and Explaining Pairwise Comparisons Between Texts
A common task in computational text analyses is to quantify how two corpora differ according to a measurement like word frequency, sentiment, or information content.
Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter
In real-time, social media data strongly imprints world events, popular culture, and day-to-day conversations by millions of ordinary people at a scale that is scarcely conventionalized and recorded.
English verb regularization in books and tweets
We find that the extent of verb regularization is greater on Twitter, taken as a whole, than in English Fiction books.
Towards a science of human stories: using sentiment analysis and emotional arcs to understand the building blocks of complex social systems
Given the growing assortment of sentiment measuring instruments, it is imperative to understand which aspects of sentiment dictionaries contribute to both their classification accuracy and their ability to provide richer understanding of texts.
Forecasting the onset and course of mental illness with Twitter data
Twitter data and details of depression history were collected from 204 individuals (105 depressed, 99 healthy).
Physics and Society Social and Information Networks
The emotional arcs of stories are dominated by six basic shapes
Advances in computing power, natural language processing, and digitization of text now make it possible to study a culture's evolution through its texts using a "big data" lens.
Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMatter
Since the shooting of Black teenager Michael Brown by White police officer Darren Wilson in Ferguson, Missouri, the protest hashtag #BlackLivesMatter has amplified critiques of extrajudicial killings of Black Americans.
Zipf's law is a consequence of coherent language production
The task of text segmentation may be undertaken at many levels in text analysis---paragraphs, sentences, words, or even letters.
Benchmarking sentiment analysis methods for large-scale texts: A case for using continuum-scored words and word shift graphs
The emergence and global adoption of social media has rendered possible the real-time estimation of population-scale sentiment, bearing profound implications for our understanding of human behavior.
Human language reveals a universal positivity bias
Using human evaluation of 100, 000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (1) the words of natural human language possess a universal positivity bias; (2) the estimated emotional content of words is consistent between languages under translation; and (3) this positivity bias is strongly independent of frequency of word usage.
