How to do YouTube video sentiment analysis for brand-insights
YouTube sentiment analysis can be very valuable for brand insights. In this blog, we discuss how you can search, find, and retrieve insights from hundreds of YouTube videos with Repustate’s video analysis tool. We also broadly explain how sentiment analysis for YouTube comments is done.
Sentiment Analysis For Youtube Videos
Marketing strategy in the age of social media listening includes uncovering brand and customer insights from YouTube videos. There are virtually millions of feelings and opinions about brands on YouTube everyday, expressed by people across all ages.
Social media sentiment analysis
Sentiment analysis is a natural language process used to analyze opinions, feelings, and emotions expressed in emails, social media posts, YouTube videos, reviews, surveys, business documents, etc. Businesses are indeed eager to mine opinions for vital brand insights to increase efficiency and brand reputation monitoring. Social media is so ubiquitous in this aspect, that platforms like Instagram, SnapChat, TikTok, and YouTube have become synonymous with brand reviews.
Sentiment analysis solutions employ machine learning models that can give granular discoveries of sentiment by using text analytics and named entity recognition (NER) tasks. A fine-grained sentiment analysis can give in-depth insight into the reason behind consumer patterns so that businesses can predict trends in purchase behaviour and plan strategies accordingly.
What is aspect-based sentiment analysis of video reviews?
Aspect-based sentiment analysis breaks down a review into smaller segments, and studies them for sentiment, thus enabling more detailed and accurate insights. Aspect-based sentiment analysis can easily help distinguish which features of a product or service are liked and which ones can be improved.
Let’s see an example
Went to Bar Chef last night and loved their drinks, especially the martinis, but the food was horrible. My nachos tasted microwaved and the calamari was rubbery.
This review needs to be analyzed at the aspect sentiment level, with further aspect insights on Drinks (martinis), and Food are revealed through the aspects of nachos and calamari.
In typical reviews, consumers often touch on many aspects of a product or service. Complaints or praise for price, quality or ease-of-use can all be mentioned in one comment. YouTube sentiment analysis first determines which categories are being mentioned and then calculates the sentiment for each of those categories. When compiled in aggregate across a large number of reviews, the strengths and weaknesses of a business' product or services surface quickly and actionable insights become obvious instantly.
How does Repustate’s video analysis tool perform YouTube sentiment analysis?
Repustate’s video content analysis tool conducts aspect based sentiment analysis on YouTube videos to deliver the most granular brand insights. It uses advanced named entity recognition (NER) to identify named entities in YouTube videos and classifies them into predetermined categories. NER classifies company names, geo-locations, things, and names of people who are mentioned in the videos. These insights thus can be used to improve marketing efforts, products, customer experience, or customer service.
Let us understand the steps involved in the process:
Step 1: Collect & prepare video/audio/image/text data
Videos are converted into text using speech-to-text transcription models and run through neural networks (NN) for audio content analysis. These NNs also discover caption overlays in videos, and if detected, they read and extract text from it. They also employ image detection for logos in background imagery.
All this video data, along with text data from the comments is collected and manually edited to remove redundancies, punctuations, gifs, emojis, etc. It is then converted in a machine-readable format (CSV, XLS, JSON) so it can be ingested into the machine learning pipeline for training.
Step 2: Apply sentiment analysis
The data is run through the sentiment analysis API for opinion mining. It quickly returns sentiment scores for each relevant topic, aspect, or entity ranging from -1 for negative emotions, 0 for neutral feelings, and 1 for positive sentiment.
Step 3: Visualize insights
Sentiment scores are presented in the form of visual reports consisting of charts, graphs and tables through a sentiment visualization dashboard.
Harness YouTube videos for business intelligence.
YouTube video content analysis in action
What does Unbox therapy think of the new PS5?
One of my favorite YouTube channels is Unbox Therapy that consists of new technology unboxings like smartphones, laptops and gaming consoles often before they are released to the public. It’s produced by Canadian Lewis George Hilsenteger, and with 17.6-million subscribers, Unbox Therapy has an incredible influence on consumer tech purchases.
In a recent video, Hilsenteger reviews and compares two of the biggest Christmas 2020 gaming console releases - Sony’s PS5 vs. Microsoft’s XBOX Series X.
This video was posted on November 6 and already has an amazing 5,750,761 views. So being a Canadian company dominated by tech heads, we figured we’d put this video through Repustate’s Deep Search for video analysis tool and pulled our some insights super quickly and accurately.
At between the timestamps 5:54 and 6:27, Hilsenteger says:
….that one the thing that gets talked about more frequently actually is the styling which is quite a bit different you have the simplest form possible (XBOX Series X) and you have an incredibly complex form (PS5 here with this tapering and these various shapes and then the lighting that pops up on the inside of the frame over here and the black and white motif i’ll just say i feel like this feels a little bit newer to me i like simple forms i could totally get behind this one to when it comes to styling i don’t think i would make my decision exclusively on that however i think if this thing (XBOX Series X) is sitting in your living room it’s probably going to command a little bit more attention from your pals than this one will if that matters to you.
Here the theme is styling in reference to the two entities PS5 and the XBOX Series X. He says that the PS5’s styling feels “complex” and “newer” and will “command a little bit more attention”. The newness comes from the product’s aspects “tapering”, “shape”, “motif” and “lighting”. On the other hand, the XBOX Series X appears “simple” and logically less new than its competitor.
On the topic of controllers at between 7:07 and 7:14 the Canadian tech influencer says:
….from that standpoint (controller) it was a little bit how can i say a little bit less exciting on the Microsoft (XBOX Series X) side because this thing is so similar to the previous generation controller.
So when it comes to controllers, the PS5 wins again as Hilsenteger goes on to point out Sony’s superior product design and newer styling.
These are all incredible brand insights that Repustate’s Deep Search Inside Video tool indexed and analysed in mere seconds. Imagine how much time you would save, and how much invaluable product intelligence you could gather, if you did this for hundreds or thousands of YouTube videos that talk about your brand? That’s where the real power and intelligence of Repustate’s Deep Search for video analysis tool lies.
Take a quick tour of Repustate's YouTube video analysis solution
How is Sentiment analysis for YouTube comments done?
YouTube comments analysis can help with vital insights for media monitoring not just for products and services but also for corporate and individuals in key positions. Sentiment analysis for YouTube comments is done in broadly 3 steps:
Step 1 - Scrapping & Preparing Youtube comments
Step 2 - Running it through Sentiment analysis API
Step 3 - Data visualization
Read more in detail about YouTube Comments Analysis
Built for social media listening, Repustate’s sentiment analysis API understands short forms, slang, emoticons, emojis, and hashtags that people use while posting comments. By assessing thousands of comments, we can bring the aspect-based sentiment of each product or service feature mentioned in the video comments.
To learn more about how Repustate can help you extract brand insights from YouTube videos,