In two days it will be a year since the inauguration of Twitter user ID 25073877. I share some insights from 2,587 tweets posted between 18/01/2018 08:49 AM EST (GMT -5) and 18/01/2017 06:53 AM EST (GMT-5).
Repository Fringe is a gathering for repository managers and others interested in research data repositories and publication repositories. I collected an archive of #rfringe17, containing 1118 Tweet IDs. I then analysed the text of the tweets with Voyant Tools to identify most frequent terms and refined the results to 230 terms.
I have just deposited the following data on figshare: Top 300 Terms in the Conservative and Labour Manifestos 2017 (Counts and Trends).
I'v deposited on figshare a CSV file listing counts and trends of 459 terms or word forms in full text of Prime Minister Theresa May's 'letter to Donald Tusk triggering Article 50' (29 March 2017).
I prepared a dataset from Twitter user with user_id_str 25073877 containing a total of 123 public Tweets and corresponding metadata between 15 February 2017 06:40:32 and 15 March 2017 08:14:20 Eastern Time.
I have archived 3,603 public Tweets from_user_id_str 25073877. I looked at the sources of those Tweets, and the top 50 most frequent terms per main source (iPhone and Android).
A quick word count of DJT's Tweets since inauguration day unitl 06/02/2017 07:07:55 AM Eastern Time.
I made a collection of Tweets tagged with #dhcshef published publicly between Monday September 05 2016 at 17:54:58 +0000 and Saturday September 10 2016 at 23:37:06 +0000 and I write a little bit about it.
This is part IV. For necessary context, methodology, limitations, please see here (part 1), here (part 2), and here (part 3). Since this was published and shared for the first time I may have done new edits. I often come back to posts once they have been published to revise them. --- Throughout … Continue reading Libraries! Most Frequent Terms in #WLIC2016 Tweets (part IV)
An update on my work doing basic text analysis of a sample dataset of #WLIC2016 Tweets.
Here's an edited list of the top 50 most frequent terms extracted from a cleaned dataset comprised of 10,721 #WLIC2016 Tweets published between Monday 15/08/2016 10:11:08 EDT and Wednesday 17/08/2016 07:16:35 EDT.
I have looked at the text from 4,945 Tweets published with #WLIC2016 since 14/08/2016 until 15/08/2016 11:16:06 (EDT, Columbus Ohio time).