An Introduction to Sentiment Analysis
One of the major benefits of using a social listening tool is that you can quickly determine how people feel about your brand or product. But Sentiment Analysis can be a subjective tool, and understandably businesses and people alike are often wary of the process of identifying the positive, negative or neutral sentiment from a comment. We've put together this guide so that you can better understand how it works and what social listening companies do to perform sentiment analysis on the data we collect.
What is Sentiment?
First we should touch on what we mean when we talk about sentiment. Simplistically, it describes the feeling that comes from within a comment or review. Is someone for or against a product? Do they think a service was good or bad? Did they like or dislike something? While sentiment is usually described as having a binary opposition it is often more complex. There are comments and reviews that offer neither a good or bad opinion, often described as a neutral opinion.
What is Sentiment Analysis?
Sentiment Analysis aims to determine the attitude of the author of a specific piece of content with respect to the topic of interest. Comments and content can be referred to as Positive, Negative, Neutral or have no sentiment at all.
How is Sentiment Analysis Conducted?
Social Listening companies have produced their own system for conducting sentiment analysis. At DataRank we use a combination of both machine learning based Sentiment Analysis and manual, human-rated Sentiment. This allows us to rate large data sets of thousands of comments, while also controlling the quality of the sentiment analysis process.
Machine based comment analysis is improving every day, but there are nuances in language that require human rating. For example, irony, satire, and sarcasm are often difficult to project in text based conversation, and therefore requires the analysis of context to determine the sentiment behind the comment.
As with many good machine-based tools, there is a margin of error, which will become smaller over time as technology improves. In the meantime however, our combination of machine and human sentiment analysis is producing some interesting and postiive results.
What does Sentiment Look Like On A Social Listening Platform?
Sentiment is an integral part of social listening and has its own tab, with multiple views, to optimize the value that a business can draw from ratings of their product or brand. It is also shown on the dashboard, and on every rated comment.
Above you can see an example of the comments view for Tide Pods. Comments that are negative are represented with a red broken heart image, comments that are positive are represented by a green full heart. A neutral comment is not shown but they are represented by a gray full heart.
Sentiment can also be viewed at a country-wide level. Comments with location meta data that also have a sentiment rating will contribute to the overall state sentiment rating. From this view a company can analyze where their product or brand is doing well, and where there needs to be some improvement.
The sentiment heat map shows where positive comments are being generated from a city level. This is a deeper level of analysis that shows specifically what areas are gathering reviews, based on the location of the comment, and the kind of sentiment that is gathering heat in that area. The map toggles between positive, negative and neutral, allowing users to get a specific view of areas that are doing well, and areas that are not doing well.
How Does Sentiment Analysis Help A Business Increase Sales?
Sentiment Analysis has many use cases in social listening. Businesses can discover at a base level whether people like or dislike their products. They can determine the sentiment around their competitor's products. They can do market research for products that they want to start producing, analyze the sentiment around a new product release, and analyze the best received marketing strategies implemented by other businesses.
Once sentiment data has been gathered businesses are able to narrow into which issues their brand needs to resolve, what they are doing right, and how they can improve on their current success.
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