How does the Citizen Science community use hashtags when discussing e-Health?

by | Jul 14, 2022 | Beta Graphical article, Graphical article, Impact & Reach, Internal Content

  Reading Time: 3 minutes
We analysed 17,122 Citizen Science tweets filtered with Health keywords in order to answer the following questions: What are the most used hashtags in the e-Health discussion? Are hashtags normally used alone or alongside others on the same theme?

SDGs is by far the most used hashtag in this discussion, followed by openscience, health, scicomm and Covid-19. The discussion about Health in the Citizen Science Twitter community seems to revolve around the Sustainable Development Goals.

People tend to use more than one hashtag in the tweet, with all topic-related hashtags forming community-like structures around certain subjects.

From the initial dataset, which contained 365,609 tweets related to Citizen Science, after applying a filtering process we obtained 17,122 tweets related to Health. From the tweets acquired we extracted all the words that were preceded by “#” to find the hashtags. Each hashtag appearing in our tweets was then counted. The results displayed in Fig. 1 show that SDGs is the most used hashtag in this topic with almost three hundred more appearances than the second most used one. With this result it seems like the discussion about health and e-health in the Citizen Science community in Twitter revolves around the Sustainable Development Goals.

Figure 1: Treemap with the 50 most used hashtags.

Once we knew what were the most used hashtags, it was interesting to discover how these hashtags were related to one another. Normally a tweet is accompanied by two or more hashtags in order to increase visibility of what is written so it would be reasonable that hashtags in the same tweet had a topic in common.  We created a graph of related hashtags, the connections between hashtags were computed by linking all hashtags in a tweet to one another. The results are shown in Fig. 2 which is a three-dimensional visualization of these connections. In this graph, the bigger and closer to yellow a node is, the more times it has been used alongside other hashtags. It can be observed how hashtags on the same topic form community-like structures and how some other hashtags act as links between these topic-communities, thereby showing themselves to be the most connected hashtags.

Figure 2. 3D view of the connected hashtags graph.

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