How YouTubers Can Use Social Media Listening to Stay on Top of Their Game


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YouTube is one of the most influential platforms when it comes to extracting market intelligence through social media listening. After all, with over 2.3 billion users worldwide, it’s easy to see why YouTube is one of the best social channels to build and engage with an audience. But with 500 hours worth of video uploaded every minute, the competition is immense. As a result, creators need to be more innovative and work harder than ever.

YouTube Video Analysis

Fortunately, artificial intelligence (AI) has opened new fronts for social media creators in staying on top of their game by helping them understand what content resonates with their audience the best. AI works for you and helps you grow your brand presence through sentiment analysis. A social media listening tool that is driven by sentiment analysis can give you the right audience insights that you need.

What is YouTube Video Analysis?

YouTube video analysis is the process that allows you to extract the audience sentiment from YouTube videos and their comments, descriptions, and other information. It does this by using artificial intelligence and machine learning (ML) algorithms to extract the main themes and sentiments around these videos.

ML algorithms use a very interesting, coordinated method to perform sentiment analysis on YouTube videos as can be seen below.

Step 1: Audio transcription.
During the first step, the videos are converted into text using speech-to-text software based on neural networks. In other words, the video’s audio track is converted to a text transcript.

Step 2: Caption overlay. During the next step, the sentiment analysis tool analyzes the video on a frame-by-frame basis and identifies and extracts any other text in the video. This, for instance, includes text on captions, subtitles, and other forms of text.

Step 3: Image recognition. Apart from identifying and analyzing text, the social media listening tool also identifies images in the video. This includes, for example, images in the background or other imagery displayed in the video. In addition, the sentiment analysis API will also identify any brand names and logos and classify them as entities.

Step 4: Text analysis. During the next step, the model will extract and process the text from the video’s accompanying post and comments by using text analytics and natural language processing (NLP). It also recognizes common social media colloquialisms, hashtags, and emojis.

Step 5: Sentiment analysis. Once all the text is extracted from the video and its accompanying comments, the sentiment analysis API extracts key topics and themes from the content as well as their respective sentiment. Here, the API will assign a sentiment score to each aspect or topic which will show whether the sentiment is positive, negative, or neutral. In the end, the tool will give you an aggregate sentiment score of your video.

Step 6: Visualization. When the analysis is complete, the model will display all the sentiment scores on its dashboard. This enables you to see and understand the results and the insights they provide.

By analyzing these insights, you’ll learn what exactly your audience wants and get insights into the content they prefer. You will also have tangible directions as to what you need to do to reach a wider audience, engage them more, and grow your channel.

How Can YouTube Creators Use Social Media Listening?

Let’s now look at how YouTube creators can leverage sentiment analysis and use social media listening to get the most value.

Understand And Engage With Your Audience Better

When you know your audience’s sentiment towards your content and what they’re saying about it on social media, you will better understand what they want and expect. You can tailor your content to meet their needs and expectations. In addition, you’ll also be able to engage with them better. Ultimately, this means that you will be able to retain your audience and attract more viewers.

Being a YouTube content creator is fun, but a stressful undertaking. Social listening analytics gives you the advantage of having an AI-powered tool that can give you clever ideas to create engaging and inspiring content whilst also helping you build a whole community around this audience intelligence through ideas like events, gathering contests, and virtual meets.

Stand Apart From Your Competition

AI-enabled social media listening will help you understand your competitors better and plan strategies on how you can differentiate your brand from them. You can learn how your competitors’ content resonates with your audience, why they like or dislike it, and how you fit into this market. With these insights, you also get to build your content more easily as well as capitalize on emerging trends.

If you use social listening analytics wisely, you will notice that you don’t need a huge budget to make great content. The main aspect of having a great online following is to make your viewers feel connected to you. Personalize your content, leverage other social media channels to gain a wider audience, check the sentiment trend periodically to see if your tactics are working, and improvise.

Build Your Brand Reputation

As a content creator, your brand value is directly linked to the content you create. Social media listening allows you to track and monitor what your audience is saying about your brand through their opinions on your content. This means that you can track changes in your audience’s sentiments and spot any upward or downward trends. This allows you to identify any issues before they spiral into a bigger problem as many YouTube stars have experienced.

Audience affections are fickle and unpredictable, especially in an age where people take offense to seemingly anything. When you identify grievances in their early stage, you can address them in a planned manner rather than a knee-jerk reaction. And because machine learning algorithms in social listening analytics also allow you to track sentiment over time, you can find the timelines when there are changes in your content’s engagement levels as well as the reasons behind them. This allows you to adjust your branding strategy and make improvements where necessary.

Identify Opportunities for Collaboration

When you have an overview of your audience profile, you can see what it is that is common amongst them apart from your brand. Social media listening platforms, when driven by AI, can tell you what the common likes and dislikes amongst your audience are, and thus help you identify opportunities for collaboration with other brands and content creators. This creative collaboration can be a valuable tool to grow your channel and expand your reach – especially if you have the right collaborations. This tactic can have a significant impact on your audience’s opinions about you.

Similarly, social media listening can tell you about smaller creators that speak positively about your content and brand. These can be valuable opportunities for collaboration and to develop meaningful partnerships. Additionally, this builds trust with your audience and allows you to grow it by attracting more viewers. You have to be mindful, though, of who is approaching you, and carry out your own due diligence because there have been cases where hackers have tried to hijack YouTuber accounts.

Create More Value

As a YouTuber, you know that there is no guarantee that every single video you create will be a hit. But with sentiment analysis-driven social media listening, you can learn what the sweet spot is concerning your audience, how relevant your content is, and what are the ways in which you can make your videos more interesting.

It’s safe to say that as a content creator, you can increase your success and grow your audience if you’re able to solve their problems, alleviate their challenges, or even thaw the mundaneness of their everyday life.

With sentiment analysis insights to drive your social media strategy, you can enhance the value of your content and showcase your skills better.


In conclusion, when you want to grow your following on YouTube, it’s crucial that you understand what your audience is leaning towards so that you can ensure that your content is relevant and interesting. When you are able to do this, you can cater your content to better meet audience needs and expectations and, in the process, build lasting relationships and loyalty with them.

Machine learning models do exactly this with acute precision and accuracy. Once they are trained, they can scan thousands of social media posts on a daily basis and extract this valuable information for you. This way social media listening can give you the breakdown of exactly what in your video brought in the most views, what your viewers would like to see more, and how you can be the best in your business.

Martin Ostrovsky
Martin Ostrovsky is the founder and CEO of Repustate. He is passionate about AI, ML, and NLP. He is responsible for guiding the strategy and success of all Repustate products by leading the cross-functional team responsible for developing and improving them. He sets the strategy, roadmap, and feature definition for Repustate’s Global Text Analytics API, Sentiment Analysis, Deep Search, and Named Entity Recognition solutions. Martin has a bachelor’s degree in computer science from York University, Toronto. It was while completing his MBA from the Schulich School of Business, Toronto, in 2009


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