Sentiment on social media is a great source for understanding what the public feels about a brand, product, or service. However, companies rarely leverage the power of social media to understand their customers’ needs.
Twitter is a public social media channel where customers can share their opinions, complaints, or compliments about a company worldwide. There are more than 450 million monthly active users on Twitter, and 350,000 tweets are sent per minute.
According to a study, 77% of users who tweet regularly state that they use the platform to express their opinions. Gathering insights from Twitter can help you understand your customers and develop new strategies to grow your business.
This article explains why analyzing the sentiment in users’ tweets is crucial for your business, the steps of conducting Twitter sentiment analysis, and its best practices.
Why analyze the sentiment in tweets?
- Twitter is the leading platform for brand engagement. So, if you want to hear from your customers or especially connect to them, checking Twitter regularly, analyzing the content, and reacting to user tweets are great actions to create a positive brand image.
Figure 1. A customer sharing her experience with Volvo cars and engaging with the brand.
- A recent survey shows that only 3% of customers tag (with @ symbol) the company’s official page when they have problems with customer service. You can reach a broader audience by analyzing the tweets that do not tag your company’s name but mentions your products, services, etc.
Figure 2. A customer tweets about the latest Amazon upgrade without mentioning the company
- Responding to customer complaints on Twitter is crucial. A recent study shows that responding to customer complaints on Twitter in an empathetic manner results in positive attitudes towards the company.
Figure 3. After a customer complaints about their flight being canceled, customer services provide support and arrange a ticket for another flight
What are the steps to conduct Twitter sentiment analysis?
The steps depend on the level of accuracy you want to obtain. If you are processing a
- a significant amount of low-value data (e.g., tweets about popular and affordable B2C products), you can skip all optional steps
- a small amount of high-value data (e.g., tweets about B2B companies selling expensive but rarely bought services)
1. Extract the data
First, you need to extract your data to work on them. You can create a developer account and use Twitter API to extract your data to another file you will be working on.
2. OPTIONAL: Clean your dataset
The data you get from Twitter is unstructured, it involves characters, unnecessary punctuation, or unrelated items such as emojis. So, it needs to be pre-processed before conducting analysis using automated tools or manual effort.
3. OPTIONAL: Annotation
You can rely on a custom machine learning (ML) model to achieve high accuracy. To customize your ML model, you would need to annotate your dataset (i.e., labeling examples with the right metadata like emotional state).
4. OPTIONAL: Train your algorithm
You need to train your algorithm with your labeled data to categorize tweets as either positive, negative, or neutral so that you can analyze the sentiment in your dataset accurately.
5. Run the ML model on the prepared data
In the case of a high-volume, low-value dataset, an off-the-shelf model could be utilized.
As performing all these steps can be labor intensive, companies usually outsource sentiment analysis services to run their operations smoothly.
Top three best practices of Twitter sentiment analysis:
1. Monitor your brand
Listening to what your customers say about your brand is crucial to stand out in the market. By conducting twitter sentiment analysis, you can assess, categorize, and understand what customers feel about your products or services. This gives you a direction about the products or services you need to strengthen and get your brand image.
2. Give quick responses to complaints
Almost 80% of Twitter users state that they feel positive about a brand if they respond directly to users’ tweets about their queries. By analyzing the sentiment in users’ tweets, you can identify negative feedback and respond immediately and try to provide solutions.
3. Understand the sentiment toward your competitors
Understanding your competitors’ market image can give you critical insights regarding the key points that lead to business success. Twitter sentiment analysis can be used to understand the public sentiment towards competitors, what customers like or dislike about them, and their strategies while engaging with them. Thus, you can understand what works best and what doesn’t.
Here are our other sentiment analysis articles if you want to learn more:
- Latest Top 5 Open Source Sentiment Analysis Tools
- Top 5 Sentiment Analysis Challenges and Solutions
- Sentiment Analysis Services Benchmarking
You can also check our data-driven list of sentiment analysis services.
If you need any assistance, do not hesitate to contact us:
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