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 Deep Search for video analysis tool.
Table of Contents
- Sentiment Analysis For Videos & Reviews
- Are YouTube videos a good source for brand insights?
- What is sentiment analysis of social media?
- What is aspect-based sentiment analysis of video reviews?
- How does Repustate’s video analysis tool perform YouTube sentiment analysis?
- YouTube video sentiment analysis in action
- Sentiment analysis for YouTube comments
Sentiment Analysis For Videos & Reviews
Does your marketing strategy include uncovering brand and customer insights from YouTube videos? If not, it should. There are virtually millions of feelings and opinions about brands expressed by people on YouTube every day. Yet, when social media sentiment analysis is talked about, most people think of Twitter or Facebook, but not YouTube. This is because the idea of extracting brand insights and emotion mining from YouTube videos seems improbable, even though YouTube might very well be the Queen of product reviews.
Are YouTube videos a good source for brand insights?
The influence that YouTube has at various stages of a consumer’s purchase journey is undeniable. Shoppers frequently use YouTube before making purchases. According to a Google/Ipsos, U.S., Shopping Motivations Study, around 80 percent of shoppers claim to have accessed a video review on the site in the early part of their shopping process. YouTube viewers watch over 219 million hours worth of review videos every year. Unlocking the brand insights buried in YouTube videos might very well be the biggest thing to happen in a very long time to social media listening, sentiment analysis, and brand insights.
Is YouTube even a social media platform?
YouTube has an astonishing 2-billion users globally. Although this video platform is very different from Snap, Instagram, or TikTok, it is similar to them in that ultimately it allows people to share video content with other users on the platform. People use it to view, upload, rate, share, add to playlists, report, comment on videos, and subscribe to other users' channels.
Content on YouTube is usually either user or brand-generated. There is a wide variety to choose from, including TV-show clips, music videos, short films and documentaries, audio recordings, movie trailers, live streams, video blogging, and educational videos. It is indisputable that YouTube is a social media platform that possesses a wide variety of brand insights hidden in its video content. When extracted, using video sentiment analysis, these findings can help brands effectively gain more awareness and drive purchase.
What is sentiment analysis of social media?
Sentiment analysis is a natural language process used to identify, extract and analyze expressed opinions, feelings, and emotions in text data. Text data is chunks of digitally produced language with a meaning intended by the author. Examples of unstructured text data are emails, social media posts, YouTube videos, consumer reviews, customer survey answers, and business documents. Brands love to mine for opinions to bring important consumer insights to the surface that lie buried in social media posts and customer surveys. Brands such as H&M, Samsung and T-Mobile want to understand how their customers feel about their brand. Whether they are looking to establish the voice of customer, conduct market research, or monitor online brand reputation, brands use these insights to improve their products and marketing and to drive sales through more effective customer acquisition, retention and overall profitability. This allows them to drive sales via more effective customer acquisition, retention, and overall profitability. In other words, emotion mining from YouTube videos or any other source of customer sentiments, is good business.
Does social media have a lot of brand insights?
Social media is the deepest reservoir of customer reviews, feelings, and opinions about brands. Billions (yes, billions) of people look to Instagram, SnapChat, TikTok, and YouTube to either broadcast how they feel about certain brands, products/services, or watch videos of other consumers and influencers talk about a variety of brands from Walmart to Balenciaga. Sentiment analysis allows you to identify and score chunks of social media posts that express feelings, opinions, and emotions as positive, neutral, or negative about any brand. Moreover, aspect-based sentiment analysis allows you to be even more granular by using text analytics and named entity recognition (NER) to discover “why” they feel the way they do about specific aspects of a brand, product or service.
What is aspect-based sentiment analysis of video reviews?
Aspect-based sentiment analysis goes one step further than typical sentiment analysis by automatically assigning sentiment to predefined categories. It involves breaking down a restaurant review into smaller segments, allowing more granular and accurate insights from the data. With aspect-based sentiment analysis, it can be distinguished which features of a product or service offering are liked and which ones can be improved.
Let’s see what happens when our reviews above become longer and more detailed:
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.
Repustate’s Deep Search for video analysis tool can conduct aspect based sentiment analysis on YouTube video content to deliver the most granular, useful, and actionable brand insights. In addition, it also conducts named entity recognition. An advanced natural language processing technique, NER uses automation to identify named entities in your YouTube videos and classifies them into predetermined categories. NER can be used to classify company names, geo-locations, things, and names of people who are mentioned in your videos. These can then be presented to you in a way that brings your videos' insights to the forefront. You can use these insights to improve your brand’s marketing efforts, products, customer experience, or customer service.
How does Repustate’s video analysis tool perform YouTube sentiment analysis?
Repustate’s Deep Search for video analysis tool extracts brand insights and performs sentiment analysis in these 3 simple steps:
Convert video to text through the use of speech-to-text models
a. These models are unique to each language and are built using neural networks
b. This yields a transcript of the speech along with the timestamps for each word
Index the text into Semantic Search for Video section by section. Video can be broken up into smaller sections based on longer pauses or changes in the speaker. By analyzing it section by section, we get enough context to disambiguate entities, but not too much content as to lose the ability to associate entities with granular enough timestamps.
We now have timestamps of video associated with entities, themes, and topics found in the text, along with the associated metadata. Performing Deep Search will now yield all matching sections, which in turn refer to snippets in the source video.
YouTube video sentiment 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 for video content analysis 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.
Sentiment analysis for YouTube comments
YouTube videos gather thousands of comments. Deriving sentiments from the text manually can be a big hassle when dealing with the numerous brand review videos. Repustate’s sentiment analysis API can help you by automating YouTube sentiment analysis. Using natural language processing and machine learning techniques, like named entity recognition, we extract the named entities and assign sentiment scores to the themes, aspects, and topics within each comment.
NER can classify brand names, company names, places, and more. Thus allowing the API to extract semantic meaning from the comments in relation to the different things mentioned in them. This gives you key competitive insights as to how you measure up to competing brands in terms of product features, returns and warranty, store locations, customer service and other areas.
Built for social media listening, Repustate’s 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, Contact Us Now to Get Started!