Using Social Data to Uncover the Regional Contexts of Mental Health Challenges

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Working at the intersection of data science, behaviour change and social impact, Ripple Research has uncovered large-scale qualitative insights on mental health in Nigeria by using a machine learning model to detect, track and connect thousands of topics actively being discussed within the wellness industry. These conversations took place across news sites, forums, blogs and social media platforms such as Twitter. Our algorithms identified dominant categories in these online discussions, then our research team developed specific lexicons to unearth the relevant opinions, sentiments and emotions relating to the topic of mental health and wellbeing. The data we gather on these conversations always indicates related sub-topics that add further nuance. For example, alongside italy whatsapp number data mental health, the data revealed tangential issues relating to social protection and poverty.

The data set was assembled from January 1 to August 15, 2021, and it revealed that various sub-topics of mental health and wellbeing garnered over 380,000 posts from 100,000 unique authors in Nigeria in that period. We were also able to trace the range of emotions and posts relating to trauma, stress, depression, re-opening anxiety, conventional anxiety and attention deficit/hyperactivity disorder. The majority of online conversations surrounding these issues took place on Twitter, where specific hashtags like #mentalhealth accrued over 20,000 tweets and over 82 million impressions over the eight-month period.

On the subject of mental health, social media acts as a clear resource for sharing details about helplines in Nigeria for those who may not be able to access clinics due to distance or financial constraints. We found that much of this online activity was led by popular Twitter accounts such as @aproko_doctor and @firstdoctorr, who have engaged audiences that are keen to share details about free, trained and licensed councilors available in the country. The following tweet is just one example.