Social media sentiment analysis is a strategic way to monitor trends and patterns in the feedback people give about your brand on different social platforms. More than 3.6 billion people actively use social media to drive conversations, and so gathering data from these social sites is a great place to start. This article gives a brief overview of how you can use social media mining and social media sentiment analysis to define a growth strategy and sense customers’ sentiment about your brand.
Once data is gathered, what matters most is how you translate it into actionable insights to improve customer experience at multiple touchpoints in the sales cycle. For this, you need to conduct sentiment analysis on all our data for insights.
What Is Social Media Sentiment Analysis?
Social media sentiment analysis is a natural language processing (NLP) technique used for understanding the emotions behind user-generated content from social media mining. It gives a clear sense of how people feel about your brand.
Social media sentiment analysis gives you insights far more detailed than just the number of likes, comments, and shares of your posts. It allows you to gather and analyze comments from the public and see if they are positive or negative. Just because your post or video has garnered 100,000 views and 400,000 comments, it may not mean that this metric is all positive, or vice versa.
Social media tactics to get the maximum number of impressions leaves out the fact that the comments and videos posted may not all be good for a company. The internet is rife with strangers getting into fierce arguments, which is bad for a brand. So for all you know, more than half of your 400,000 comments could be people who are saying things against your brand. Without sentiment analysis of these impressions, there is no way a brand can know where they stand in the public eye just with empty metrics of number of likes and comments.
A social media sentiment analysis tool that can objectively and precisely analyze emojis, hashtags, comments, and even video content through video AI, will give you the exact picture of your social media performance brand metrics.
How Is Social Media Sentiment Analysis Done?
Social media sentiment analysis is done in four stages.
- Platform Identification The first includes identifying the social media platforms that you want to conduct social listening on.
- Data Collection The second is extracting the social media data through live API integration like you can do on Facebook or YouTube, or through data scraping as on Instagram. This will give you insights into new trends and also keep a tab on your brand reputation through checking all your mentions and scouring the root of the issue if the mentions are negative.
- Data Analysis The third stage is where sentiment analysis is conducted on text as well as video data. This is crucial because it can help you keep a close eye on the kind of people following you and study account demographics, evaluate influencers, and even spot potential brand ambassadors.
- Data Visualisation In the fourth stage, all these insights are presented in a dashboard where you can set alerts for real-time notifications for keywords or brand mentions, and even see the correlation between customer emotions and different aspects of your brand.
Why Do We Need Sentiment Analysis On Social Media?
Sentiment analysis of social media data can tell you if customers truly like you or not. This is far beyond empty numbers in a metrics tool. If they share your post, if it is because they are writing a positive review, or because they are tagging you to be sarcastic? An intelligent social media sentiment analysis platform can identify emojis, and this means, you will never get false positives from sarcastic comments. Most tools neglect emojis in comments because they are not text.
Similarly, suppose there are hundreds of comments in hashtags, you can sieve them for positive and negative emotions. Not only that, through the insights from your tool you can also classify user accounts that share common interests and create targeted brand activities. These and many more benefits can be garnered from the application of sentiment analysis on social media listening.
Some of the benefits of social media sentiment analysis are listed below:
- Discover new market trends
- Design targeted marketing campaigns
- Track brand awareness
- Develop a personalized brand experience
- Conceive new product ideas
- Discover and use influencer marketing
- Develop more engaging online content
- Monitor competitors
What Are the Challenges of Social Media Mining?
Social media mining carries many challenges such as the volume and quality of the data itself. Add to this, the difference in multimedia formats can pose a limitation. Data security is also a critical factor. Let us examine these and more issues that can arise in data mining.
- Volume
Social media mining involves extracting large volumes of data from multiple social media platforms. It can be challenging to put these big data sets into meaningful categories to understand your customers. The large scale also means that the solution for sentiment analysis needs to have a high speed of processing capacity.
- Security
When you’re handling large data sets, you need to be mindful of data security threats. Data breaches and leaks can compromise valuable customer information and ruin brand reputation as consumer information can be highly delicate.
- Multimedia
Raw social media data is in multiple file formats. For instance, Facebook data is in text, video, and image files, while Instagram data is primarily videos and images. Sorting data and extracting insights in these multimedia formats can be tedious and time-consuming.
- Text Overlay On Video
When analyzing visual channels like TikTok for valuable data, you need to extract meaningful insights from caption overlay and dialogue. Repustate’s social media listening tool helps you categorize these insights from audio data via speech to text, and analysis, text overlay for videos and background images from branded content.
- Entity Identification
Entity identification automatically classifies key elements in data sets into predetermined categories or entities like location, product, person, and organization. With large-scale multimedia data, it becomes difficult to identify and extract relevant entities from a pool of diverse data formats.
Social Media Sentiment Analysis – The Repustate Advantage
Repustate helps you carry out effective social media listening and gather helpful information to drive decisions. With our text analytics tools and multilingual sentiment analysis, you can get easy, accessible insights at scale.
- Sentiment Analysis Dashboard for Data Visualization
You can track analytics and measure your performance on different social media platforms from one place. Whether it’s TikTok, Twitter, Facebook, or Instagram, you can monitor all conversations simultaneously. With a single button, you can view data on keywords, trending hashtags, brand mentions, and more.
- Real-Time Social Media Listening
Never miss out on relevant conversations on your preferred social media platforms. Our real-time data capabilities track brand mentions as they happen. It empowers you to resolve issues quickly and boosts customer experience for your clients.
- Competitor Analysis
With Repustate, it is easy to know how you measure up against the competition. More than viewing relevant insights on your brand, you can also track conversations about your competitors for comparative analysis.
- Social Listening From Audio or Video Stream
You have access to not only text data but also all mentions on streaming channels and social media platforms. We provide deep-level insights on brand mentions in other media formats with astute audio and video content analysis capabilities.
- Stock Market Sentiment Analysis
The stock market can be a competitive and cut-throat industry. High-frequency trading algorithms search for any disruptions in the market and use them in sub second transactions. Having accurate information at your fingertips means that you can make the right call on any given trade.
- Customer Trend Analysis
Repustate interprets existing trends to reveal the behavior patterns of your customers. You can track customer experience information over defined periods, and figure what likes and dislikes are common amongst your customers.
With the right sentiment analysis model, you can effectively interpret data from social media mining. Thus making it easy to define your brand’s messaging and growth strategy around things that your customers care about. Our social media listening solution will help you understand not only your customers but also your competitors.
