The Networks of #liberconference on Twitter (updated, July 7, 2017, 13:15 pm EET)

This is the network analysis that we are doing with Giannis Tsakonas and Sergios Lenis in the context of the Twitter presentation of LIBER’s Annual Conference 2017 taking place in Patras, Greece, July 5–7, 2017. LIBER is the European network of research libraries and LIBER’s Annual Conference is one of the most important gatherings for research library professionals. It is organized since 1971 and runs annually on a different European city. With the advent of technology and social media, the LIBER Annual Conference has gained a significant exposure on the digital sphere of professional publicity. In 2016, the Finnish organizers in Helsinki had counted a number of 4300 tweets with the hashtag #liber2016. The conference has one main track that runs three days, which is preceded by some pre-conference activities three days before.

For our purposes, up to this very moment, 13:15 pm EET, July 7, 2017), we have collected 3,746 tweets based on the search terms @liberconference, #liberconference, #liber2017 and #liber17 in the period since June 30, 2016. These tweets were written by 210 Twitter users (who are going to be referred as “tweeple” from now on).

Of course, this a preliminary dataset and the only reason that we are displaying the outcomes of these Twitter network analyses is in order to facilitate spreading among the members of the LIBER community the worth of the social media analysis focusing on the digital transactions of their field. As a matter of fact, in our closing presentation at the 2017 Patras LIBER Annual Conference, we are going to present the analyses of the present dataset of tweets around the #liberconference.

The following plots correspond to a number of different time series that we have counted in the dataset:

The time series of the 3,746 tweets.
The time series of the 210 tweeple.
The time series of 3983 mentions.
The time series of 4517 hashtags.
The time series of 1351 embedded photos.

Moreover, we have counted the following 95 languages (one of which was undefined)

The top 20 hashtags (in different days) were the following:

A sentiment analysis of the content of these tweets has revealed the following scores when the tweets were grouped in the hashtags they were including:

The subjectivity score of the sentiment analysis of tweets grouped in hashtags.
The polarity score of the sentiment analysis of tweets grouped in hashtags.

Furthermore, the visualization of the graph of co-occurring hashtags is:

The graph of co-occurrent hashtags.

Next, we have explored the graph of mentions among tweeple, which is shown in the next visualization. Yellow coloured nodes (and edges) are tweeple who mention other ones (“mentioners”), blue coloured nodes (and edges) are tweeple who are mentioned by other ones (“mentioned”) and red coloured nodes (and edges) are tweeple who both mention and are mentioned by other ones.

THOSE WHO WANT TO ACCESS DIRECTLY THIS ZEPPELIN NOTEBOOK IN ORDER TO ABLE TO USE ALL THE COMPUTATIONS/VISUALIZATIONS WE HAVE DONE HERE IN AN INTERACTIVE WAY, PLEASE GO TO:

URL: http://150.140.171.51:9980/#/

User Name: liberconf

Password: liberconf

Access will be granted after 4:00 pm EET, July 7, 2017.