Social Media Sentiment Analysis: Everything you Need to Know

It is almost too obvious to point out that there are many opinions that are exchanged within the social media world. While there is an almost unlimited number of opinions and ideas that you can find, there are probably some certain topics or profiles that you want to pay special attention to in terms of analyzing sentiment. Does your target audience like a new product you just launched? Or what do people think about your brand or company? Perhaps you just want to know what how people feel about a particular football team.

While reading through dozens or even hundreds of posts and comments may be the first approach you think of taking regarding determining what people think, this is a time-consuming, if not imprecise way, to gauge opinion. Therefore, if you want to take a more data-based and scalable approach to finding out what people think on social media, then social media sentiment analysis is a worthwhile type of analysis. Social media sentiment analysis is an important analytical approach for many companies, brands, and influencers since it can help them analyze the opinions or feelings of their target audience efficiently. But what exactly is sentiment analysis in social media, and how can you use it to help you understand opinions? 

In this article, we will begin by discussing what sentiment analysis is and its core benefits. We will then move to explaining some limitations of social media sentiment analysis, while emphasizing the need to use it as part of a multifaceted social media analytics strategy. Finally, we will walk you through how to conduct a sentiment analysis for social media using a specific example while highlighting important points to keep in mind.

What is Social Media Sentiment Analysis?

So what is the core purpose of conducting a sentiment analysis on a specific social media network? In reality, sentiment analysis for social media goes beyond counting mentions or likes in that it captures the emotional tone of conversations, assigning them as positive, negative, or neutral. Social media sentiment analysis is all about understanding how people feel when they talk about a topic, whether it is a sports team, a product, or even your brand/company. By diving into the sentiment and feelings that are communicated in tweets, reels, stories, and posts, you can gain valuable insights into how people feel towards particular topics.  

Sentiment analysis that focuses on a defined set of social media data is a great way to assess and understand on what people are thinking about a certain topic on a large scale. With so many posts, comments, and mentions being created every day, looking at these big data sets can help you understand how people may feel broadly about certain topics while giving you the benefit of a large sample size. By labelling the content as positive, negative, or neutral, sentiment analysis helps you spot meaningful patterns in what might seem like a large and diverse group of opinions. 

One of the main benefits related to sentiment analysis on social media is its efficiency. Instead of spending hours manually reviewing thousands or even millions of interactions, automated tools can quickly process and categorize data, giving you a clearer picture of your audience’s overall mood and opinions. This makes it a really effective way to keep an eye on your brand’s health, spot potential crises, and find out generally how people feel about specific topics. 

Another advantage is its versatility. Sentiment analysis can be applied across multiple social media channels such as Facebook, YouTube, Twitter, Instagram, and TikTok, as well as the broader web, allowing you to get a holistic view of public sentiment. Sentiment analysis used as a tool for social media analytics can empower businesses to make data-driven decisions, whether it’s refining their messaging, enhancing customer service, or planning future campaigns. By understanding the emotional pulse of your audience, you can adapt and thrive in an ever-changing digital landscape. Moreover, it can help you uncover not just what is being said but how people feel about it, specific to the platform they’re using. For instance, Twitter might reveal immediate reactions to a campaign, while Instagram sentiment might focus more on visual appeal. Understanding platform-specific sentiment lets you adapt your strategies more effectively to each network’s unique audience and trends. Along these lines, it is important that you use a social media tool that allows you to analyze different networks as well as dozens or more profiles you are interested in.

Don’t forget that social media sentiment analysis should not be considered only as a part of analytics for your own posts or those of others you are tracking. When used as part of a social media monitoring strategy, sentiment analysis can also help you detect what others think about your brand and company if you are not tracking their profiles, or they are not mentioning your profiles directly. Ultimately, social media sentiment analysis features as part of a social media monitoring tool can be beneficial to seeing what people think about your brand or business. 

Limitations on Social Media Sentiment Analysis

While sentiment analysis on social media is a great way to efficiently find out what people think generally on a number of topics, it isn’t without its limitations. One of the main issues is that it often provides a high-level analysis, focusing on broad trends rather than a deep, nuanced understanding. For instance, a social-focused sentiment analysis might focus only on social media platforms like Facebook or Twitter, missing out on wider opinions about your company or brand from offline sources or other print media.

Another issue is that human emotions are complex and feelings can be expressed in different ways. Sentiment analysis divides opinions into three categories – positive, negative or neutral – but not all sentiments fit neatly into these categories. Moreover, the algorithms that support sentiment analysis software can get sarcasm, humor, and context-specific expressions wrong, which leads to inaccuracies. On top of that, the sentiment you get from social media data might be swayed by a few vocal minority groups, who might not represent the overall sentiment of your audience.

This is not to say that sentiment analysis on social media does not have its uses, but that you should always understand how your data might be skewed. Moreover, you should treat sentiment analysis as one of the many tools you use as part of a broader social media analytics approach. Sentiment analysis used in conjunction with other methods like surveys, focus groups, and user analysis can give you a better overall picture of what people think. By using a range of research tools and strategies, businesses can get the best out of sentiment analysis and get a more complete view of their brand’s reputation and audience engagement.

How to do Social Media Sentiment Analysis: Your “How-To” Guide 

While the picture we painted of social media sentiment analysis initially appears fairly straightforward, the task of using it to meet your needs is another matter. But don’t despair, we are going to walk you through some different ways in which you can use sentiment analysis. Conducting a sentiment analysis for social media can actually mean a number of different things, depending on what you want to accomplish. In reality, there are various ways you can go about running a sentiment analysis based on what you are interested in and how you want to present the data. When using a social media analytics tool to analyze sentiment, there are most likely going to be many options related to what metrics to track and analyze, as well as how to track your results. 

Before delving deeper into what is possible with a sentiment analysis tool, it is important to keep in mind the sources of your data. In setting up your sentiment analysis, you need to first decide on 3 things that will define your data set: what networks you are interested in, the profiles that you are analyzing, and the time framework for analysis. Ultimately, the choice is up to you and what you want to analyze, but you should be aware that changing the networks, profiles, and timeframe will alter your data set.

In helping show you everything that is possible with social media sentiment analysis, we want to run through some scenarios about the different ways you can use this type of approach. The goal is to present concrete examples regarding the different ways you can analyze the sentiments related to specific profiles and networks, as well as the various ways you can display your data. The National Football League (NFL) is by many metrics the most popular sport in the United States, and has also been growing in popularity around the world. Therefore, we want to conduct a sentiment analysis on some of the posts, as well as comments about those posts, for the following teams (one team is selected from each division): Atlanta Falcons, Dallas Cowboys, Minnesota Vikings, New York Jets, Kansas City Chiefs, and the San Francisco 49ers. The timeframe of analysis will be from September 1 to November 31, 2024.

Below, we will see a number of images that help illustrate the different formats and ways you can analyze and present your data. These are generated by the Fanpage Karma social media tool and throughout our analyses we will look at the following social media networks: Facebook, Instagram, TikTok, Twitter, and YouTube. To start our analysis, let’s look at a simple bar graph that illustrates overall sentiment of posts for all the social media networks and profiles we listed previous within the designated timeframe. While this might not be the first analysis you want to take for your sentiment analysis due to its broadness, it is a good starting point to show you one of the types of analysis you can do. 

This is a simple bar graph that groups that total number of posts made across the social media networks listed above in the designated timeframe. The posts are categorized as either positive, negative, or neutral. As you can see here, the overwhelming majority of posts made by these team profiles were either neutral or positive. 

Now we can move to conducting sentiment analysis of Twitter data related to the profiles in our study. Metric tables are a great way to get an overview of the positive and negative sentiment of posts in comments. In utilizing a metric table, you can analyze the positive and sentiment of posts either by counting the total number of positive or negative posts or through by calculating the share (percentage) of positive and negative posts.

Let’s start with a relative simple Twitter sentimental analysis example, as shown in the metric table below. We are looking at both the total number of, and share of, positive and negative Twitter posts from the teams’ profiles for the timeframe we specified above. This helps give us an overview of the sentiment of posts for these Twitter profiles. Moreover, since we are using a social media analytics tool that allows us to track other metrics, the last column shows the overall number of Tweets for this period as wells. This allows us to see whether or not there is an adequate sample size to make us more confident in our conclusions. 

We can also conduct a Tweet sentiment analysis that looks at just the overall share of positive and negative Tweets that are coming from these profiles. Below, we will look at both the share of positive and negative Tweets from these profiles visualized in a bar chart. The highest share of positive Tweets comes from Kansas City followed by the Minnesota Vikings. Please note that the percentage of positive and negative Tweets does not equal 100% since we have not included the share of neutral posts in our analysis. 

(Share of Postive Tweets)

Interestingly, as shown below, Kansas City has the highest share of negative Tweets in this period even though it also has the highest share of positive Tweets as well. The Dallas Cowboys have the lowest share of negative Tweets related to its profile.  

(Share of Negative Tweets)

Let’s now move on to an example related to conducting Facebook sentiment analysis for the profiles above. We will start similarly to the Twitter sentiment analysis and begin by analyzing a metric table. However, in this case, we will expand the scope of the metric table and look at data for not only the posts coming from the teams’ profiles but also the comments of those posts. As we can see below, there is a lot to take in when it comes to analyzing the sentiment associated with these profiles.

Interestingly, the Kansas City Chiefs have the highest total of both positive and negative comments from their Facebook posts. This is tempered by the fact that they also have by far the most overall number of positive comments out of any team. In terms of the post text themselves, the Kansas City Chiefs and San Francisco 49ers have the highest percentage of negative sentiment, while the Kansas City Chiefs also have the highest share of positive posts for its profile.  

To contrast with the Twitter sentiment analysis above, we will now look at positive comments from the various posts on the teams’ Facebook posts for the given time period. Instead of a bar graph, as was the case in the Tweet sentiment analysis, we will use a line graph that does a good job of visualizing how the accumulative total of good and bad comments grows over time.   

(Total Number of Positive Comments)

As shown above, in terms of the count of positive comments, the Kansas City Chiefs profile has led the way from the beginning and sits comfortably ahead of the other profiles. As we then turn our attention below to the number of negative comments above posts from these profiles, we see that the Dallas Cowboy profile has quite a bit more negative comments on their Facebook posts. 

(Total Number of Negative Comments)

Now that we have shown a way to look at sentiment trends over time, it may be interesting to move on to YouTube and how social media sentiment analysis may work on this network. For instance, perhaps you are interested in undertaking YouTube sentiment analysis on videos you are posting and want to see what people think about them. Unlike the Facebook sentiment analysis above, for our YouTube sentiment analysis we will view the share of comments in bar chart form to find out which team profiles have the highest share of positive and negative comments. Below, we see that the Kansas City Chiefs have the highest share of positive comments for their profile by a relatively wide margin

(Share of Positive Comments)

We can then turn to the negative share of comments below. It terms of the share of negative comments on videos posts by these teams, you see that the New York Jets have the highest, followed by the San Francisco 49ers. Again, the positive and negative share of positive and neutral comments does not equal 100 since the share of neutral comments in not shown in these bar charts. 

(Share of Negative Comments)

In the last several examples, we have looked at metrics on a profile basis. But perhaps you want to look further into the share of positive, negative, and neutral comments are for all social media profiles in your data set on a particular social media network. In order to better illustrate this, let’s say we wanted to conduct an Instagram sentiment analysis related to the the posts that NFL teams are making. In this case, we will not focus on the sentiment associated with the posts or comments on a specific team’s profile, but rather bring together all of the data and look at whether a social media network, in this case Instagram, trends toward positive, neutral, or negative. As you can see below for our Instagram sentiment analysis, the vast majority of posts from these teams are either neutral or positive in sentiment.

Lastly, let’s look at some of the other metrics we can bring into a social media sentiment analysis study to show how this can be beneficial. To illustrate this, we will conduct a TikTok sentiment analysis for our target profiles. Below is a metric table, similar to some of the others we have presented above. However, alongside the number of positive and negative share of comments on TikTok for the 6 NFL teams, the final three columns show the number of posts and average engagement and post interaction rates for the profiles in the same time period. In this case, we can better assess the overall performance of these profiles and how these metrics may correlate with certain sentiment analysis metrics. The point we want to emphasize is that during your sentiment analysis you don’t need to limit yourself to only the sentiment analysis metrics we detailed above, but can also bring in other key metrics.

One last thing to mention is conducting sentiment analysis as part of social media monitoring. We have detailed the importance of social media monitoring before and how it helps to monitor mentions of your brand that are not directed toward your profiles. If you are using a social media monitoring tool, it can be helpful to have sentiment analysis functions as part of it, since one of the points of social media monitoring is that it helps you better understand opinions of people that are related to your brand. If you are dealing with hundreds or thousands of posts of your brand online, then sentiment analysis can be a helpful and efficient way to understand what people think.

As we have demonstrated above, there are a number of things to take into account when using social media sentiment analysis. Finding the right social media sentiment analysis tool that allows you to also find content optimization opportunities and benchmark yourself against your competitors is important. Due to the number of social media tools that offer sentiment analysis as a feature, it would be useful to provide a little more detail about how to assess different tools on the market to find the right one for you. 

Features of the Best Social Media Sentiment Analysis Tools

Now that we know the possibilities, and limitations, of sentiment analysis, let’s talk a bit about what you should look for in a sentiment analysis tool and how exactly you can use one to help you better understand opinions. Generally, a sentiment analysis feature will come as part of a broader social media analytics and benchmarking tool where you can perform several different types of analyses in terms of comparing your own profiles against competitors and also finding content optimization opportunities. However, when searching for a social media sentiment analysis tool, the first thing you should confirm is that it covers the social media networks you are looking for. Second, and related to the first point, you should also make sure that the tool allows you to track as many profiles as you need. Keep in mind that many social media tools limit the number of profiles you can track and analyze. Luckily, there are tools that also allow for unlimited profile tracking. 

Moreover, as we have already mentioned, there are many other useful analytic analyses that should go along with a sentiment analysis. These include various content optimization approaches as well as competitor analysis and benchmarking capabilities that relate to your comprehensive analytics strategy. Lastly, when discussing social media monitoring sentiment analysis, it is also useful to be able to track and analyze instances when your brand or company is mentioned on the web or in groups that you are not monitoring. Social media monitoring tools are generally used for this activity, and sentiment analysis can be a useful form of analysis when attempting to find out what people thinking about your brand.

In summary, if you are searching for social media sentiment analysis tools online, you should be asking yourself these questions to make sure it gives you what you need:

1. Does it allow me to analyze the social media networks I need?
2. Can I track as many profiles as I want?
3. Are there other analytical features that come with it?
4. Is there an option for analyzing the sentiment of mentions of my brand or company online, beyond social media networks? 

The Fanpage Karma Social Media Sentiment Analysis Tool

As we have discussed above, social media sentiment analysis can be a useful approach when attempting to understand the opinions of people on various topics. The power of this type of analysis lies in the fact that it allows you to analyze hundreds or even thousands of posts and comments quickly and efficiently. However, keep in mind that sentimental analysis is just one way to analyze social media data and should be considered as one approach out of many that can help you understand trends, opinions, and preferences of your target audience. Therefore, when are researching sentiment analysis tools for social media, it may make sense to search for an “all-in-one” social media tool that allows you to not only conduct sentiment analysis, but also gives you powerful analytical and benchmarking features. 

So, if you are searching for the right social media sentiment analysis tool that gives you the ability to analyze multiple networks and an unlimited number of profiles, you can try Fanpage Karma’s free 14-day trial to find out if it is right for you. Don’t forget that, in addition to sentiment analysis, Fanpage Karma also offers industry-leading analytics and benchmarking capabilities along with community management, content planning, monitoring, and research features.

You can also sign up for the free weekly webinar to find out more about sentiment analysis as well as other functions of the Fanpage Karma social media tool.