#overlyhonestmethods analyzed: tweets about reproducibility

Screen Shot 2013-01-10 at 11.44.00 PMSince the hash tag #overlyhonestmethods went viral, I have been checking tweets for reproducibility and replication issues. Many tweets are in some way connected: every time a researcher admits being ‘creative’ about getting significant results or slightly ‘polishing’ tables and figures, it will be harder to check or replicate their results. Some tweets, however, directly refer reproducible results. Here they are:

Reproducibility

23 tweeters directly used a form of the phrase reproduc*. Newest first:

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About this search

Above, I included all tweets that came up when searching for reproduc* among tweets between Day 1 (January 7, first tweet by dr_leigh) to January 9, 5.17pm. While I saved and looked through these, already 600 new tweets were sent. While I’m writing this blog post there are 965 new tweets. I did not read these updates (yet). I collected tweets for the same time period on “replication” separately.

First and newest tweet

The first (ever) tweet introducing #overlyhonestmethods (my starting point) is by pharmacologist/neuroscientist @dr_leigh, and the newest one included here is by PhD student in public policy @straightedgersx (January 7pm, 5.17pm).

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3 thoughts on “#overlyhonestmethods analyzed: tweets about reproducibility

  1. [...] Since the first #overlyhonestmethods hash tag was used on January 7, 23 tweets include concerns or jokes about reproducibility. I summarize them here. [...]

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  2. [...] collecting #overlyhonestmethods tweets about reproducibility and replication. For me, those two terms describe the same issue. Whenever data were manipulated, [...]

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  3. […] In early January, the twitter hashtag #overlyhonestmethods revealed the current state of replication and reproducibility in the sciences. Thousands of researchers tweeted about obscure p-values, data manipulation, p-value fishing and the lack of transparency. The ‘confessions’ and cynic remarks were hilarious, but a bit unsettling. Political and social scientists mainly tweeted about: citing papers they haven’t even read; pleasing reviewers with stupid requests; manipulation of p-values and data; “please don’t replicate my study”; qualitative and mixed methods intransparency; “my supervisor told me so”; I don’t know what I’m doing! I collected the main tweets about replication and reproducibility. […]

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