Transitioning to renewable electricity generation is an important component of the US response to climate change. The speed of this transition depends on factors ranging from the rates of technological innovation, market adoption and governmental incentives...
New preprint from our group: https://arxiv.org/abs/2205.15937 We know spending time outside is good for our health, and maybe more so in March 2020 than ever before. Dogs were psyched. But confusing and contradictory public health messaging complicated access to natural spaces...
New on the arXiv: “Ousiometrics and Telegnomics: The essence of meaning conforms to a two-dimensional powerful-weak and dangerous-safe framework with diverse corpora presenting a safety bias” https://arxiv.org/abs/2110.06847 We measure essential meaning using language as the map. Some definitions: 1. Ousiometrics: The quantitative study of the essential meaningful components of an entity, however perceived. 2. Telegnomics: The far sensing of knowledge (~ distant reading) ...
"Sentiment and structure in word co-occurrence networks on Twitter" New preprint from our group led by @uvmcomplexity postdoc @MikaelaFudolig Using tweets containing #imwithher or #crookedhillary, both relating to Hillary Clinton's presidential bid in 2016, we explore the relationship between context and sentiment through word co-occurrence networks. ...
“Augmenting semantic lexicons using word embeddings and transfer learning” New preprint from our group led by Thayer Alshaabi https://arxiv.org/abs/2109.09010 In prior work, we surveyed internet people for their emotional response to words. Surprising no one, we found "hahaha" consistently reflects the good vibes. ...
We have a new paper, interactive visualization, and data platform. Nutshell: we’ve curated 100 billion tweets over 10 years to produce day-scale rank/frequency time series for n-grams in over 100 languages. It’s a whole big thing. A short thread—The paper: “Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter” ...
"Blending search queries with social media data to improve forecasts of economic indicators" New preprint led by Yi Li & Adam Fox from @mmdatascience w/help from our group https://arxiv.org/abs/2107.06096 This work extends a model recently proposed by Dingdong Yi, @ShaoyangNing, Chia-Jung Chang, & S. C. Kou in their paper "Forecasting Unemployment Using Internet Search Data via PRISM" ...
“Say Their Names: Resurgence in the collective attention toward Black victims of fatal police violence following the death of George Floyd” New study from our group in collaboration w/ @reharp @foucaultwelles @ryanjgallager. https://arxiv.org/abs/2106.10281 The murder of George Floyd in May 2020 sparked international protests, renewed attention to #blacklivesmatter, and set several records for online activity. ...
Sirius: A Mutual Information Tool for Exploratory Visualization of Mixed Data by @artistjaneadams, @todddeluca, @ChrisDanforth, and @peterdodds of @uvmcomplexity and Yuhang Zheng, Konstantinos Anastasakis, Boyoon Choi, Allison Min, and Michael Bessey of @massmutual Link to paper: https://arxiv.org/abs/2106.05260 Github Repo: https://github.com/compstorylab/sirius Through a partnership with @mmdatascience as the MassMutual Center of Excellence in Complex Systems and Data Science at @uvmcems, we had a question: How can we create better visualization tools for high-dimensional mixed data exploration to better understand complex health? ...
