New preprint:

“Computational timeline reconstruction of the stories surrounding Trump: Story turbulence, narrative control, and collective chronopathy”

arxiv.org/pdf/2008.07301…

P. S. Dodds, J. R. Minot, M. V. Arnold, T. Alshaabi, J. L. Adams, A. J. Reagan, and C. M. Danforth Some questions to ask yourself and others:

What happened in the world over the last two weeks?

What about this time last year? Two years ago?

And what order did the major events happen in?

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”

arxiv.org/abs/2007.12988

Thread for a new paper of ours on the arXiv:

“Ratioing the President: An exploration of public engagement with Obama and Trump on Twitter”

arxiv.org/abs/2006.03526

J. R. Minot, M. V. Arnold, T. Alshaabi, C. M. Danforth, P. S. Dodds We explore the dynamics of how Twitter users have responded to tweets made by Obama and Trump from their main accounts, @BarackObama and @realDonaldTrump.

New NCOVID-19 paper thread:

“How the world's collective attention is being paid to a pandemic:
COVID-19 related 1-gram time series for 24 languages on Twitter”

Main site:
compstorylab.org/covid19ngrams/ We make two main contributions:

1. We curate and share usage time series of 1,000 1-grams that have mattered in March of 2020 (words, emojis, hashtags, etc.) for 24 languages.

We hope other researchers can use these time series to connect with other data streams.

“Noncooperative dynamics in election interference”

New publication from our group in Physical Review E

journals.aps.org/pre/abstract/1… Led by @d_r_dewhurst and inspired by Russian interference in the 2016 election, we simulate the timeless competition between red and blue

Now, we stretch out words naturally when we speak.

But stretched words (sometimes called elongated words) are fairly rare in book and other text corpora, and they aren’t represented well in dictionaries (if at all).

So we thought, let’s science this. Stretchfulness in written text arrived in an abundant, accessible source with Twitter (along with the possible end of civilization but that issue is beyond the scope of our current project).

Dataset: 10% of all (140 character) tweets from September 2008 to the end of 2016.

New paper threeaaad!!!

Soooooo, we went exploring for stretchable words on Twitter, and we uncovered a strange and amusing realm of language:

“Hahahahaha, Duuuuude, Yeeessss!: A two-parameter characterization of stretchable words and the dynamics of mistypings and misspellings” Stretchable words are undeniably real:

1/5 Op-ed in @nytimes uses Google n-gram data to claim "most religious and spiritual words have been declining in the English-speaking world since the early 20th century.” 2/5 While this statement could certainly be true, raw n-gram data is not able to support the claim due to underlying non-stationarity. The author is likely referring to trends like figure 5h in the original Culturomics paper, “God” is decreasing.