Like you, I’ve read the news today. Like so many others out there, I also wanted to write something. This is a personal reflection.

I’ve just published a translation of an interview with the slain Mexican journalist Javier Valdez at Nieman Storyboard (Neiman Foundation for Journalism at Harvard University).

A reflection on Open Access Outputs as Potential Educational Resources.

No Trumpian Tweets coming from the Web Client since 25 January this year; no Tweets from Android since 25 March. Tweets from Twitter Ads have made an appearance alternating with Twitter for iPhone Tweets since 31st March. In the 18 days of May so far, the account has tweeted every single day, totalling 90 Tweets until the morning of the 18th of May.

I have just deposited the following data on figshare: Top 300 Terms in the Conservative and Labour Manifestos 2017 (Counts and Trends).

I will talk about online Graphic Medicine at the Pint of Science event: Humans and technology: in life and in death. Tuesday 16 May 2017- Doors open 6.30 PM, Event 7.00 PM – 9.30 PM.

I am looking forward to participating in the event titled “Digital Humanities/Humanidades Digitales/Informatica Umanistica. An Intercultural Dialogue” that will take place on Thursday 20 April 2017 in Rome, at the Political Science Department of the Università degli Studi Roma Tre.

I have now prepared and shared a CSV file containing Tweet IDs and other metadata of 3,805 Tweets from user ID 25073877 posted publicly between Thursday February 25 2016 16:35:12 +0000 to Monday April 03 2017 12:51:01 +0000. I discuss source counts, trends and implications for research.

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).