If your business is just growing, you need to know what your customers expect from you and then do your best to match their expectations. From the specifications in demand for the services after the consumption of the product; everything is crucial when it comes to customer loyalty. Businesses are turning towards social media’s help for analyzing the ‘unofficial’ reviews about the products or services.
Even in political campaigns and social changes, sentiment analysis is essential when going forward with these measures. CNN, MSNBC, and other media outlets have been devoting a large chunk of their time in analyzing the tweets shared by the 45th president of the US. The Obama administration was known to have used sentiment analysis to my public opinion during the 2012 campaign. Before legalizing LGBT marriages in Ireland and Australia, surveys were conducted extensively to know public opinion on this issue.
This just goes on to show how imperative sentiment analysis is, not just for organizations and governments but also for any major movement to take effect.
Social Media for Sentiment Analysis
With more and more millennial using social media, they are susceptible to sharing their opinions on these platforms as well. Twitter is one of the largest platforms where people share their views on many topics. Many people believe that they get to know about massive news headlines such as natural disasters or riots in a certain city before the local media outlets alert the public. With the use of Python, Machine Learning is helping in the analysis of emotions among the masses. Machine Learning is a key factor for strengthening the various tools for sentiment analysis.
This is why there is a growth in people choosing Machine Learning and Python programming language as a career choice and taking tutorials to learn the subject. There are already numerous courses available for Machine learning and Python, and one such course is ‘Learn Python Programming from Scratch’. It is a free online tutorial which gives you insights into the basics of Python Programming language, syntax, functions, data structures and much more for FREE!
Businesses keep a close eye about what is being said or discussed regarding their product or services. The addition of hashtags becomes incredibly helpful when looking for a specific topic.
For example, experiences of people with Uber can show up on twitter with the hashtag Uber. This allows the hashtag to become a portal to see all the other tweets associated with Uber. If a customer had a rough experience with the service, Uber will detect it with the hashtag and take the necessary precautions to ensure it’s not repeated. Hashtags are also used on platforms such as Instagram and Facebook and serve the same purpose on these websites and applications as well.
Best Tools for Sentiment Analysis
1. Quick Search
Quick Search offers a quick analysis of your brand and how it is doing online. Being a social media search engine, it offers coverage on all social media platforms and even forums, blogs and news media. Some of its features include:
- Identifying upcoming trends and promote or boost your content
- Key Performance Indicators that matter such as engagement, demographics, geographies, and sentiment
- Benchmark against competitors by comparing multiple brands
Brands that wish to know how their product or service is used in the market and how their customers are reacting to it, this tool is extremely handy. Posts on social media and reviews posted online can be identified and analyzed along with official documents and publications. It also helps in getting to know the hot topics that are trending today, get feedback on their products and expand their business.
You can find out how people react to your brand and products and you can segregate them further. With the use of filters, you can identify these people with their location, income, and gender. This can also be done with the use of specific keywords. Terms such as ‘awesome’, ‘love it’ and ‘thanks’ shows positive sentiment. Emojis that appear as happy face, applause or thumbs up are seen as affirmative.
This tool enforces a detailed and multilingual analysis of content from many sources. It helps in understanding if the feedback is positive, neutral, negative or impossible to detect for sure. Phrases are identified and compared on the basis of the relationship between each other and is then evaluated. It has several features including:
- Analyses opinions expressed in tweets, reviews and blog posts
- Identifies opposite opinions and those that seem ambiguous
- Distinguishes between objective facts and subjective opinions
- Determines comments which might appear ironic
- Can rate comments that are highly positive to brutally negative
- Does very well in identifying the sentiment of each sentence
This open source tool for Twitter sentiment analysis is extremely helpful when you need to pull the tweets out from last week. You can see individual tweets from identified Twitter users and note their position on the sentiment spectrum. There are several benefits of this tool, such as:
- The emotion behind each tweet is identified and color-coded, such as blue for negative and green for positive
- Clustering tweets according to the relevant topics with the help of machine learning algorithm
- Words that could specify an emotion used once or multiple times
- Finding location from where the tweets were posted
The tool struggles with slang and detecting sarcasm. However, for a free tool, this is one of the best for analyzing emotions of a twitter user.
Top Companies which Provides Sentiment Analysis
Founded in 2012 in Ireland, the company extracts the potential of the data. Their text API which is known mainly as AYLIEN text analysis API allows users to find the sentiment of their brand. It also analyses documents and blogs to summarize large amounts of data.
Here is a good website which you can refer to learn more about APIs used in Machine Learning.
Brandwatch has become one of the largest tools for analyzing and monitoring social media platforms. It was founded in 2007 in the UK and is now used by many companies, and agencies to analyze and capture social media communications.
Being one of the oldest companies in this sector, it has become the world leader in creating innovative natural language processing based text mining for high-value knowledge and decision support. The company was founded in 2001 in the UK and is currently being used by many top commercial and governmental organizations including the top 9 pharmaceutical companies. It can be used to mine a variety of text resources such as patents, clinical trials, news feeds, and propitiatory content.
Founded in 2005 in the US, the company puts customer feedback to work. It is a key player in finding out why customers feel the way they feel and powers real-time front line response and business optimization.
With 20+ years of experience, the company is known to enhance the customer experience by detecting the overall ‘tone’ of the customer. This helps them keep an edge over their competitors and knowing their customer perception, they can create strategies to give their customers a better experience.
Sentiment analysis is the best way to keep an eye on your users and advance your strategies to expand your growth. With more companies taking this seriously, it’s clear that customer first will be the core of any strategy and meeting the demands of the customers is the only way to skyrocket your business.