Sentiment Analysis: Business Insights that Help you Grow
The most actively growing part of the web is 'social media'. With the proliferation of opinion rich blogs, reviews, social networks and other forms of online expression, online opinion promises to equip enterprises with ‘real insight’ into what is driving people, and what they really think.
Hard to ignore these consumer voices, companies are increasingly using Sentimental Analytic techniques (more easily described as ‘social media monitoring’ or ‘online consumer intelligence’) to identify emerging trends and their implications for the reputations of people, companies and products.
The swift eruption of activity in the area of ‘Sentimental Analysis’ can thus be attributed to the surge of interest in exciting new computational information-gathering tools and systems; that can study opinions, sentiments and emotions in text.
In a new research, Indiana University researchers stated “The millions of messages sent daily via San Francisco-based Twitter can help predict moves in the Dow Jones Industrial Average by analyzing sentiment.” By scouring tweets for key words and analyzing them using an algorithm the researchers had developed to divide the mood of Twitter users, and were able to predict the daily up and down movements of the Dow during a period in 2008 with 87 percent accuracy.
Why Sentimental Analysis or Opinion Mining?
It is hard to ignore the huge volumes of opinionated text floating around the web. Most businesses align their decision-making process with this important piece of information – “What other people think”.
In the past, individuals and businesses would gather opinions from friends and family and surveys, focus groups and consultants respectively. But with the explosion of the Internet and Web 2.0 platforms such as blogs and various other social media, consumers are making their brand experiences and opinions available, good or bad regarding any product or service. Expressing therefore on a global platform, these consumer voices have the power to wield enormous influence in shaping the opinions of other consumers – and ultimately, their brand loyalties and purchase decisions.
Extracting Meaning from Text
Sentimental Analysis can help extract meaning from articles and conversations, and automatically perform detailed statistical analysis to identify emerging trends and their implications for the reputations of people, companies and products.
An Example Review
(Cited by Bing Liu from University Of Illinois at a Text Analytic Summit)
'I bought an iPhone a few days ago. It was such a nice phone. The touch screen was really cool. The voice quality was clear too. Although the battery life was not long, that is ok for me. However, my mother was mad with me as I did not tell her before I bought the phone. She also thought the phone was too expensive, and wanted me to return it to the shop. …”
We observe here - Opinions, Targets of opinions, and Opinion holders. Based on the overall sentiment expressed by opinion holder, the sentiment can be either positive or negative. In this case positive, nonetheless an opinion can also be expressed for the component or a specific attribute of the product.
Feature based Mining Summary
‘I bought an iPhone a few days ago. It was such a nice phone. The touch screen was really cool. The voice quality was clear too. Although the battery life was not long, that is ok for me. However, my mother was mad with me as I did not tell her before I bought the phone. She also thought the phone was too expensive, and wanted me to return it to the shop. …”
Feature1: Touch screen
Positive Opinions:212 (in numbers)
The touch screen was really cool.
The touch screen was so easy to use and can do amazing things.
Negative Opinions: 6 (in numbers)
The screen is easily scratched.
I have a lot of difficulty in removing finger marks from the touch screen.
Feature 2: Battery Life etc...
Comparison Review Generated Using Sentimental Analysis
Key Benefits of Real-Time Sentiment Analysis
By using Sentimental Analysis to monitor exactly what has been said about, in the above case- the iPhone, technology can measure the success its post-launch activities and determine whether or not a specific product improvement is needed. Largely, the key benefits include ways to -
- Help companies keep on top of issues and respond to trends impacting on business.
- Gather new customer insights from
unstructured-content (gathered from social networks).
- Determine the degree to which a sentiment is positive, negative or neutral for the entire content or a segment of the content.
- Identify those voices and publications influencing customers and competitors.
- Adjust and optimize communication strategies.
- Use it to direct strategic decisions such as modifying marketing messages, customer service or product development.
- Receive early warnings of market developments.
- Manage and preserve brand equations and reputations.
The fact that humans often disagree on the sentiment of text illustrates
how big and difficult a task it is for computers to get this analysis right. The shorter the
string of text, the harder it becomes. Harder, but worth it!