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Found 8 papers, 4 papers with code
An assessment of measuring local levels of homelessness through proxy social media signals
An increase to the log-odds of ``homeless'' appearing in an English-language tweet, as well as an acceleration in the increase in average tweet sentiment, suggest that tweets about homelessness are also affected by trends at the nation-scale.
Curating corpora with classifiers: A case study of clean energy sentiment online
Both of these drawbacks could be overcome with a real-time, high volume data stream and fast analysis pipeline.
Sentiment and structure in word co-occurrence networks on Twitter
We explore the relationship between context and happiness scores in political tweets using word co-occurrence networks, where nodes in the network are the words, and the weight of an edge is the number of tweets in the corpus for which the two connected words co-occur.
Augmenting semantic lexicons using word embeddings and transfer learning
Sentiment-aware intelligent systems are essential to a wide array of applications.
Quantifying language changes surrounding mental health on Twitter
Mental health challenges are thought to afflict around 10% of the global population each year, with many going untreated due to stigma and limited access to services.
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.
The growing amplification of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020
We find that for the most common languages on Twitter there is a growing tendency, though not universal, to retweet rather than share new content.
The shocklet transform: A decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series
We introduce a qualitative, shape-based, timescale-independent time-domain transform used to extract local dynamics from sociotechnical time series---termed the Discrete Shocklet Transform (DST)---and an associated similarity search routine, the Shocklet Transform And Ranking (STAR) algorithm, that indicates time windows during which panels of time series display qualitatively-similar anomalous behavior.
Physics and Society Data Structures and Algorithms Signal Processing Data Analysis, Statistics and Probability
