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Have you ever heard the term ‘global twitter heartbeat’? Global marketers will die to get it right for the sake of building a strong and efficient sentiment analysis system for their product. It’s utterly an imaginary concept if your business has an online presence and sentiment analysis isn’t a part of your social media marketing strategy. State of the art marketing institutions do not leave a single stone unturned for social media data mining to keep their social media monitoring tools well fed.
Simply, it’s the subjective impression hidden beneath a piece of text. Speaking English, sentiment analysis or opinion mining is the process of knowing the polarity of the feelings of people by analyzing the emotional baggage found in their opinionated free text surfacing over the world wide web. In the broader scale, sentiment analysis is all about aggregating the right datasets and analyzing them to extract the pattern of their thinking and the root cause behind such thinking.
Today’s bleeding edge marketing strategies are hungry for informed decisions and sentiment analysis is one of the core sectors today for designing the same. Admittedly, the optimal quality of the derived insights solely depends on the analyzing process(read approach). The process includes analyzing tools, targeted business vertical and the most important, quality of the mined data from the ever-expanding volume of big data.
If the social data mining is the first step of the sentiment analysis process then it’s for sure that the quality of the data determines the quality of the insights.
This is the obvious question. So, what’s the right data? Admittedly, it depends on some elemental factors of any data analytics process. The business vertical you are targeting, your approach to analyze the data, type of insights you are zeroing on, all of these factors play an equal role in deciding the right chunk of data you need.
As of now, sentiment analysis chiefly deals with the social media data. So, social data acquisition or data aggregation should be your the first stop. So, if you are in dire straights about the exact volume of data for mining, it’s valid and justified. To, clear the mist you need to focus on some questions first.
There are different types of social textual data available on the web. News, blogs, reviews, opinion and others. Each of the text formats carries their own essence and purpose with them. Firstly, most of the news articles are mainly subjective and their purpose is to spread awareness regarding a particular incident or product or else. Secondly, blog articles carry a versatile purpose. The aim of the most of the blog articles is to share a deep understanding regarding a particular aspect of a product or incident or else. Thirdly, reviews are one type of micro blogging techniques mainly targeted to the usage report of any product, incident or service.
So, each of the textual formats should be mined for different purposes of sentiment analysis. So, in this digital arena where the web is getting more interactive through social media platforms, reviews are getting more exposed and at the same time more essential too.
Meaningful interactions with the users can help a product to reshape itself to a more versatile one. Benchmark services or products can not be designed overnight. Usually, from the launching to the stage of becoming the benchmark a product or service goes through several rigorous modification stages and thankfully, social media reviews push the entire process to a grand success.
Now, business vertical is one of the prime movers for your data mining tool. Being a web crawling solution for enterprises we have faced diverse situations. Data is there for all but every bit of big data doesn’t carry the same importance aspect for all of the business verticals.
Likely, there are custom data products for each of them. One of our products namely, Site-specific web crawling is custom made solution where data gets extracted from a list of targeted websites.
On the other end, mass-scale crawl is for those who are looking to crawl data from a large number of websites where the source of the contents is many. Clients who opt for this particular product want to crawl data from hundreds of blogs, news, or forum sites to extract very high-level information like article URL, date, title, author and content, mass-scale crawls will provide this data in a structured format as continuous feeds. We bet, there are thousands of custom data products as big data is getting bigger and purposes and demands of different business verticals are becoming more complex and varied.
Personally, for any data analysis process, the tools are the field and the data is the seed. So, if your seed is genetically wounded you can’t expect a healthy fruit from it despite the field being adequately fertile. So, having the right datasets is more important before analyzing them and extract any sort of informed sentiment.
So, where do you want to start? I bet, it should be the single question, ‘do I have the right data for sentiment analysis’?
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