12/12/2016

What does @ddjournalism look like on Twitter?

 

Sonic Social Media, operated by Wasim Ahmed, is a company that provides social media support to organisations, individuals, journalists, and celebrities, with all aspects of social media curation and monitoring. That is, from the creation of accounts, to management and monitoring. We recently launched a call for journalists and Twitter influencers to deposit their Twitter ID here and receive some free analysis into their accounts. And one of the accounts deposited was that of @ddjjournalism. Therefore, in this post we take a look firstly at the @ddjjournalism Twitter account, and then the #ddj hashtag.

To begin, we created a network graph based on the Twitter handle ‘@ddjjournalism’ which displays the Twitter activity of the account over the previous seven days or so. See figure 1 below:

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Figure 1: Network graph of @ddjjournalism (see full report here).

The visualization looks great, but you may be asking, what does this all mean?

The top left hand side of each group is labelled, for example, G1 refers to ‘Group 1’ and G2 refers to ‘Group 2’ and so forth, and the keywords relate to the most frequently occurring per each group. NodeXL network graph reports also produce a number of other metrics such as the most frequently shared URLs, Domains, Hashtags, Words, Word Pairs, Replied-To, Mentioned Users, and most frequent tweeters. These metrics are produced overall and also by group of Twitter users. By looking at different metrics associated with different groups (G1, G2, G3, and so on) you can see the different topics that users may be talking about.

We can also take a look at the six types of network structures from  Smith, Rainie, Shneiderman, & Himelboim (2014) as a guide for interpretation.

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Figure 2: ‘Six Types of Network Structures’

Looking back at figure 1, we can now see that many of the groups resemble a broadcast network. That is, users are sharing articles that have been published on the website, and their followers are retweeting these.

Next, we decided to take a look at the hashtag ‘#ddj’ to examine some of the top influences and popular content associated with data driven journalism.

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Figure 3: Network graph of ddj (full report here).

We can then take a look at some of the top influences (ranked by betweenness centrality):

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Figure 4: Top influencers ranked by betweenness centrality.

The figure above displays a number of influencers, ranked by betweenness centrality, related to the hashtag ‘#ddj’, which includes YouTube, the Financial Times, and individuals sharing ddj related news.

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Figure 5: Most frequently occurring URLs.

Data Driven Journalism’s recent survey, which sought information on the current status of data journalism, was among the most popular URLs that were shared within the previous week or so.

We used Twitonomy to chart some analytics that look at the most frequent days of the week and hours of the day that the @ddjjournalism is most active.

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Figure 6: Days and hours of the week most active.

As the figure above shows the most active day for the @ddjjournalism account is Thursday, and the most popular time for sharing content is 10am.

Learn more about Sonic Social Media here.

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