In the second of a two-part blog series, we look in depth at how Tumblr data captured by Nexalogy and DataSift social media platforms can inform drug makers as they seek to understand and support users.
In the last blog, we discovered how the blend of the Nexalogy social data analysis platform and the DataSift social data platform is being used to yield Tumblr insight and reveal patient perspectives of mental health medication. It’s time to deep-dive into how they do it.
The Nexalogy team first analyzed mental health medication conversations in the areas of psychosis and depression. Collecting Tumblr data for a five month period identified 6,036 posts containing discussions around medication and related terms.
The Nexalogy Nexamaster platform was initially used to visualize the discussion taking place around this medication (see Figure 1, below). Abilify, a medication indicated for psychosis and major depressive disorder, is a frequently mentioned concept among Tumblr users discussing mental health. Moreover, it is most frequently mentioned in conjunction with ‘antidepressant’, ‘function’, ‘emotion’, and ‘commercial cartoon’.
To quantify activity levels, the team identified the top words being mentioned in Tumblr blogs relating to mental health and charted their frequency (see Figure 2, below).
Figure 2: Frequency of mention in Tumblr mental health blog posts
Abilify has multiple indications (schizophrenia, bi-polar disorder, major depressive disorder), but the conversation taking place in Tumblr regarding Abilify during the five-month period focused on depression.
Nexalogy and DataSift were then used to look deeper for meaningful insight. Analysis of the posts and people behind these words and concepts helped determine what young people were talking about.
Reblogs show thirst for information on depression treatment among young users
Tumblr’s ‘Reblog’ feature allows users to easily republish someone else’s blog post. This way, the content has the potential to spread incredibly fast. Not every piece of blogged content spreads at the same speed or to the same breadth of users. Therefore, looking at the speed and breadth of any content’s spread tells us a lot about what users find most useful.
When the team looked at the frequency of discussion about the topic on Tumblr, they saw clear peaks and valleys (see Figure 3, below).
Figure 3: Frequency of discussion regarding depression in Tumblr
Two posts in particular drove the wave of reblogs, and they both used the same piece of content; an FAQ about antidepressants (see Figure 4, below).
Figure 4: Content used in blogs that were reblogged frequently
The use of humour spread the message and helped resonate with the young target audience. This content was reblogged tens of thousands of times from an initial group of blogs, including this, this and this.
Key insights from the deep dive
Analysis of Tumblr reblogging activity provides three key pieces of insight:
1. Tracking reblog activity uncovered intense interest in depression treatments among Tumblr users. Aside from highlighting the need for information among a younger demographic of people, it also demonstrates the efficiency of Tumblr as a channel for drug makers to target audiences.
2. By medical communication standards, the content about antidepressants that generated reblog activity was incomplete. Despite the basic content, its popularity highlights a need to provide information on this topic. Looking at just this content, readers would likely conclude that their options for treating their depression are limited to drugs called SSRIs. SSRIs are not effective for everyone, and patients considering treatment should be aware of the full range of possibilities.
3. The format of the popular post (text as images, with a humorous tone) works for a younger audience. If you want to know how to create content for a younger audience, see what’s spreading on Tumblr.
Understand how your message is being received
Four of the top words in the Tumblr blog data were part of the same popular post: cartoon, commercial, beenwandering, purgatoilet. Two Tumblr users, ‘Been Wandering’ and ‘Purgatoilet’, had posts that featured an animated gif of an anti-depressant commercial (see Figure 5, below).
Figure 5: Animated gif of a TV commercial for anti-depressant medication
Been Wandering posted it, and this generated close to 170,000 “Notes” on the post. Purgatoilet reblogged it, and that generated another massive amount of notes. Looking at this activity provides two key pieces of insight:
1. Analyzing the 200,000+ “Notes” shows that the ad delivered the key messages of ‘depression treatment’, ‘mental health’, and ‘Abilify’. It also showed that most of the ad was well received by this audience—invaluable information for anyone creating future depression treatment ads.
2. The popularity of the Been Wandering and Purgatoilet posts alone meant that this ad reached a far broader audience than it would have through traditional media alone.
Drawing it all together
This case study provides practical examples of how the data captured by social media platforms can inform drug makers as they seek to understand and support users of their products. As we have demonstrated here, social media has a unique ability to drive efficiency while providing important insights into patients’ concerns.