What Is Opinion Mining? How is Web Scraping Involved?

Customers are now more active and aware than ever. They often express their opinion about a product or service on social media platforms and engage more in online surveys or product reviews to tell others about their experience with a particular brand.

Keeping an eye on customers’ feelings, thoughts, or opinions is essential for businesses to achieve their goals. However, with more than 59ZB of data being consumed, copied, and created each day, it becomes challenging to manually monitor and analyze every customer’s feedback. That’s when businesses use opinion mining.

Opinion mining is a natural language processing (NLP) method that enables businesses to understand customers’ feelings and opinions in less time and less cost. The term is often used interchangeably with customer sentiment analysis, but there is a slight difference between both.

This article will discuss opinion mining, how it’s performed, and some standard techniques businesses use.

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What Is Opinion Mining?

learn about opinion mining

Opinion mining resembles sentiment analysis in various aspects. So what is the definition of opinion mining? The simplest opinion mining definition is that it uses text analytics and NLP techniques to understand customer opinions on different topics and the drivers behind these sentiments.

An opinion is typically a view or perception of an individual about a product, service, or brand. These opinions can be broadly mined or extracted using text analytics tools that help analyze these thoughts present in unstructured text form.

Businesses use plenty of sources for opinion mining, such as social media platforms, reviews, online forums, feedback forms, survey responses, call center transcripts, etc. However, opinion mining through social media is considered a “volunteered” or “consented” source of gathering consumer opinion. So what is opinion mining on social media platforms? It refers to extracting customers’ comments, likes, reviews, and shares about a brand. Social media users already know that their data is getting mined, so the process is entirely ethical.

Opinion mining is a valuable tool for businesses that help them determine customers’ needs, demands, and expectations from their products and services. You can also take a competitive advantage with these insights by planning your strategies ahead of time.

Often used interchangeably with sentiment analysis, opinion mining is very different from it. Sentiment analysis is the predecessor to the opinion mining industry that examines how consumers feel about a specific topic. On the other hand, opinion mining digs a little deeper into knowing the drivers behind their opinions — what makes people think the way they do.

How To Perform Opinion Mining

know to perform opinion mining

Many businesses search for “how to do opinion mining” online and struggle with creating a process since it’s a bit technical. However, understanding the difference between a text that shows a feeling and the other that displays an opinion is critical. Semantic analysis helps to decipher these texts.

Typically, people express their feelings and opinions quite differently from how they speak. Thus, businesses use various NLP tools to identify opinions hidden in texts, extract them, quickly analyze the findings, and prepare a report of their customers’ and prospects’ opinions.

Opinion mining tools create a comprehensive consumer profile based on real-time sentiments of people and opinion analysis. In addition, several opinion mining techniques and types help business professionals perform the process more efficiently. Some popular types of opinion mining include the following.

Aspect-based sentiment analysis

Organizing the collected data is crucial in making the entire process successful. The same applies to opinion mining too. To perform a more effective analysis, you’ll have to organize the text about your product or services into different categories.

For example, if you’ve extracted customer feedback and want to analyze it, you can categorize these texts into different aspects, such as “Features,” “Performance,” “Durability,” “Usability,” “Shipping,” and more. Then, you can move forward to analyze each customer’s opinion as positive, negative, or neutral. That’s known as aspect-based sentiment analysis.

This method would interpret the sentiment: “This product has a superb performance level” as a positive opinion about the aspect of “Performance.”

Fine-grained sentiment analysis

Opinion mining categorizes people’s opinions and comments depending on the scale of opinion polarity, such as positive, negative, or neutral. However, you can get more detailed about your opinion mining process and prepare categories with the fine-grained sentiment analysis method.

This method includes categorizing and analyzing comments and opinions on a broader scale, including:

  • Very positive
  • Positive
  • Neutral
  • Negative
  • Very negative

These categories are denoted by stars in surveys and polls. For instance:

  • Very Positive = 5 stars
  • Very Negative = 1 star

You can track social media sentiments, analyze open-ended survey responses, and categorize these texts into predefined opinions with a text analysis tool. That’s how you can turn qualitative data into quantitative.

Emotion detection

This opinion mining technique focuses on finding and extracting specific customers’ emotions, such as happiness, satisfaction, anger, frustration, disappointment, and more, from the text. Various emotion detection tools work on “lexicons,” which refer to the vocabulary of a language that may include the exact words used for different things.

For instance, “Bonjour! Hola! Ciao!” are different ways to say hello in French, Spanish, and Italian. Similarly, one word can portray a negative emotion and a good emotion. For example, “Your product is a badass or killer.” That makes the emotion detection process quite challenging.

In contrast, advanced machine learning algorithms empower text analysis programs to learn directly from the collected sample text.

By using such programs, business analysts can better understand the tone of the human language and even detect whether someone used a specific word sarcastically or seriously.

Multilingual sentiment analysis

Multilingual sentiment analysis is a complicated yet broad phenomenon that requires plenty of resources and prepared software. While you can easily find some resources like lexicons online, others may be hard to find, and your software development team would have to build them.

However, some advanced language classifier tools powered by machine learning and NLP can automatically detect multiple languages of a text. Then, you can use an opinion analyzer to categorize the text into your desired language and analyze it further.

Opinion Mining: The Role of Web Scraping and Proxies

role of web scraping and proxy in opinion mining

Web scraping to perform opinion mining is a common way to learn about customers’ sentiments and thoughts. Web scraping tools include web scrapers that extract data from websites, turn raw data into valuable information with machine learning, and make it easier to perform data analysis.

Web scraping collects consumer data from different sources for deeper insights into opinions and sentiments, saving you both time and money when opinion mining. However, web scraping can become complicated quickly if you don’t exactly know what you’re doing or how to build one.

The expert team at Scraping Robot can take away all the hassle of web scraping! No more blocks, captchas, proxy management, or browser scaling. They have simple pricing, no monthly commitment, and your credits never expire.

But how can proxies help you when it comes to opinion mining? It’s simple, a proxy shields your real identity from different websites, protecting you from potential IP blocks and accelerating the web scraping process. As a result, your traffic will look more like it’s coming from a regular human being and not a bot!

The three main types of proxies are:

Data center proxies

Data center proxies may not offer as much protection from website bans as the other two types, but they’re reliable, fast, and utilizes a diverse proxy pool. The Blazing SEO team can go over options with you and help you find what type or combination of proxies will work best for your project or use case.

ISP proxies

ISP proxies are truly the best of both proxy worlds. They’re issued by actual Internet Service Providers but housed in data centers; they have the authority of residential proxies and the speed of data center proxies. In addition, blazing SEO puts no limits on bandwidth or threads, meaning more significant savings for you!

Residential proxies

Residential proxies are considered one of the best proxies for web scraping. These proxies shield your real identity with an IP address of a residential home that’s not yours. Making your traffic appear more human-like to websites. Not only do these proxies have high authority, but they’re always ethically sourced and have advanced features like geo-targeting and sticky sessions.

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Final Thoughts

conclusion on opinion mining

Opinion mining is a crucial tool that helps businesses better understand their customers’ and prospects’ opinions about specific aspects of their product or brand. This process works interchangeably with sentiment analysis and helps companies determine what their customers like, why they feel like this, and what needs to be done to improve users’ experience.

Who uses opinion mining? You should know that every type of business can use it to gather consumer data through web-scraping, whether small or large. Both Scraping Robot and Blazing SEO can make opinion mining even easier on you and your team, getting you that critical information from your customers. Reach out today!

The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.

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