Emotions are also measured. Some things you should know about the
Imagine that you are in a large chain of lecturers and suddenly a customer arrives and after showing a TV says: “The TV that you sell here is of poor quality” What is it that immediately comes to mind? Probably, almost certainly, this situation makes you think or at least reflect on the suitability of continuing or not buying. The reason is that it has detected a clearly negative opinion towards the product.
If we transfer this same situation to the Social Networks, it goes without saying that the impact of any affirmation, whether positive or negative, is magnified reaching millions of people, and can end the reputation of any company.
Precisely if there is something that Social Media has achieved is empowering the citizen, by serving as a platform where he can openly present his opinion towards a product, service, character or company in question. How many times has a small tweet generated a clear rejection in the network crossing the online world? Think a second …
But there is more, as the increasing use of these media has brought to the forefront of a much-needed discipline in data analytics. This is the analysis of feelings or also known as the analysis of opinion and serves to identify, through the processing of natural language, text analysis and computational linguistics, information that allows us to understand what is the exact intention of a message.
In general terms we could say that it allows to determine the attitude with respect to a subject, in front of a product or determined situation.
What is the use of Big Data and Sentiment Analytics?
Sentiment analysis is therefore a very valuable tool for organizations because it allows obtaining quality data to improve business strategies, facilitating the management of online reputation and making decisions in real time, for example: before the dreaded crisis of online reputation.
You can also obtain relevant information to facilitate the purchase of a product and that leads us to make strategies to seduce the client, giving a greater perspective to the companies on what to do and what not. Surprising, right?
Precisely those companies that have sentiment analysis within their strategy draw conclusions and make concrete decisions based on the information they achieve, being able to post a posteriori actions before a problem in fields as important as the customer experience or build more successful messages from the marketing department or department.
Also called Opinion Mining, Sentiment Analysis has today a very important application in the field of social networks and is currently one of the hottest topics in the field of information, for the applications it is generating.
The techniques are mainly focused on the processing, search or extraction of subjective information, trying to classify the texts automatically and cataloging them according to the positive or negative connotation of the language.
Sentiment Analysis tries to translate human emotions immersed in social data into more or less measurable indicators, but also focuses on internal or company-specific data, allowing to know efficiently what is said about a brand or product and being able to , Follow the opinions of different influential users, or simply detect trends in the network.
Four are the ways or approaches in the analysis of sentiment: keyword location, lexical affinity, statistical methods and techniques at the concept level, having different indicators:
Currently there are numerous tools capable of detecting trends in Social Networks through data from different sites in the network that allow a greater understanding of what is being discussed and identify opportunities