Sentiment Analysis Captures Insights for the Entertainment Industry

The entertainment industry, like any other industry, needs to analyze the feelings customers have about their products, whether a book, film, TV show, piece of music, or a play.

For instance, in the case of films, it would be very helpful to a film production company to understand at a highly granular level the audience’s reactions: If a comedy, what was the overall assessment of how funny it is? What are the funniest bits? What actors were liked best? Which characters had the best lines? And other similar items.

Besides the quality of the film itself, a film production company needs a deep understanding of the success of film marketing campaigns. How much response is a marketing campaign having? How are the different age groups responding? Any differences in how women and men respond? What kind of reactions do the actors’ pre-opening interviews provoke? How are the tie-ins being received? All of this information pours in from multiple sources, particularly, of course, from social media.

The film industry also faces a very rapid marketing cycle. First weekend proceeds for a film are of critical importance, so producers, analysts, and marketers need comprehensive, real time analysis of how their product is being received.

How Sentiment Analysis Can Help

Sentiment Analysis, also known as opinion mining, is a technology that detects likes, dislikes, emotions, and opinions and is often applied to social media, reviews, blogs, forum posts, chats, and similar sources. Sentiment Analysis is especially well suited for mining online content to extract insights into audience emotions and preferences.  Here’s how:

• Buzz: At the very basic level, Sentiment Analysis identifies the various mentions of an item such as a film title, a character’s or an actor’s name, and makes it possible to track those over time. A film company can monitor the number of mentions of these items over time and be alerted if the number of mentions suddenly goes up. A high level of buzz could be good, but it could also be bad, as when a film or film-related ad or tweet becomes unintentionally controversial or the object of widespread criticism. A recent example of the latter was Liam Neesom’s unfortunate interview given for his latest movie, which resulted in a Twitter storm of revulsion. In addition, studying the buzz of other, competing films released around the same time can give you insight into how effective your marketing is.
• Likes and Dislikes. Sentiment Analysis detects positive and negative sentiment around an item such as a film or actor.  At a very basic level, it identifies positive and negative language.  At an advanced level, through what is known as Entity- and Aspect-based Sentiment Analysis, it pinpoints the specific aspects that those positive and negative sentiments are about.  For instance, customers may love one of the actors, but be very disappointed with the others.
• Intent. Advanced Sentiment Analysis detects language suggesting sentiment-based actions like intent to purchase or boycott as well as both positive and negative recommendations. Again, attitudes to any aspect of an entertainment piece – the director, the cast, the plot, etc. – need to be tracked so any potential positive and negative resulting actions can be understood and mitigated.
• Large Data Sample. Advanced Sentiment Analysis can be scaled to Big Data size, making it possible to process massive amounts of data in real time.  Naturally, the larger the amount of data and the faster it can be processed, the more reliable, useful, and timely the insights and the corresponding responses will be.  Particularly for films, the marketing cycle is very quick and only Sentiment Analysis can provide very large scale, curated information in virtually real time.
• Analytics. Advanced Sentiment Analysis normalizes the extracted information, thus enabling data aggregation and quantification to provide the overall view of a large collection of content.  A dashboard presents multiple views of the sentiment information through various types of interactive graphs and charts. Sentiment data can be sliced and diced as desired, for instance by positive and negative aspects, and if desired, the user can drill down to the source text for inspection and further analysis. Other useful charts show sentiment evolution over time through a sentiment timeline.

In summary, in today’s fast changing consumer environment, where there are so many market pressures and competition is fierce, entertainment content providers turn to social media for insights into audience and overall market trends.  Sentiment Analysis is the AI-based technology for the modern age.  It helps the entertainment industry perform more cost-effective and accurate market research into their audiences’ reactions and attitudes.