TV and film reviews - Narrative analytics reveals actionable unknowns
(Maps viewable on desktop only).
Through LLM-based narrative analytics, we’ve mapped 9,764 Reddit posts about Netflix's Stranger Things as a demonstration of how the conversation around a movie or series can be leveraged as actionable data - in a way that traditional social media analysis can not. By hovering your cursor over the dots below, you can browse the content within an easy-to-understand narrative map.
Axes of the map: Inside the making of the story vs Outside viewer reaction. Personal reactions vs Popular culture. The 5-cluster level shows the general “shape” of the content. The center cluster is important – revealing that relatability of the story/characters/themes is essential to the experience. None of the clusters or axes are pre-set – they are unique to this dataset and empirically formed, factoring trillions of possible cluster/axis combinations. The is a key feature of narrative analytics: the ability to treat large samples of unstructured language - data that would normally be interpreted subjectively - and understand it empirically.
Now go to the detailed 25-cluster level - by moving the slider on the lower right of of the map, and read on.
Move slider to adjust level of detail
Comparing/contrasting narrative footprint: by episode
The chart below is the same map, but with the dots coloured based on the episode. Click or double click to view specific episodes - as you will see they have distinct narrative footprints
Sentiment by narrative: A more actionable, better contextualised view of sentiment
By cutting sentiment by narrative, we can see which conversations drive negative vs positive sentiment. We've selected a few specific clusters within the above map and shown how the sentiment scores are distributed for each narrative. As you can see from the bar graph below, some are more positive, some more negative. Some like "Season & episode critiques" have a high proportion of top-box/positive sentiment, and relatively low negative sentiment. Others, like "Plotting the plot" have higher incidence of posts with negative sentiment, and lower incidence of positive sentiment. "Climax" is the most polarised - with high negative as well as positive sentiment.
Narrative traction - what narratives earn engagement?
Narrative traction is an essential measurement - a way to understand how 'sticky" one narrative is versus another. Measured via Reddit score, the narrative with the highest traction - is "Strength under Duress". "Movement, location and metaphysics" gets comparatively less traction as a narrative. Though it is Reddit and people tend to assume Reddit is a great environment for deep, nerdy, technical observations, the data suggests this is not the sticky part - at least within this subreddit. Worth nothing that the same narrative scored relatively low on sentiment as well.
This can be actionable data not only for how a film or series is marketed. Compared to focus groups, this can also yield better, more empirical understanding of what themes and tensions within the plot resonate most strongly, as inspiration for the development of sequels or subsequent episodes. Note: you can not measure this with existing research or via social listening approaches.