Sentiments have been with us ever since Eve was enticed by the serpent to eat the forbidden fruit. Sentiments have driven us and our activities. Positive, negative, neutral or even mixed - each sentiment forms a core of our activities.
Even in this digital era, sentiments of online users make or break brands, celebrities, businesses and even personalities of individuals. Understanding the feelings of online users, broadly referring to sentiment analysis, has become critical. And for this, a custom software development company can build a sentiment analysis solution.
The Wikipedia Page Defines Sentiment Analysis As:
“It refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study effective states and subjective information.”
In simple words, it refers to analysis of whether people generally like or dislike something. Also known as ‘opinion mining’, sentiment analysis is the process of knowing the emotional tone for any particular subject, by analyzing the usage of words, which help in understanding attitudes, opinions and emotions used within an online mention. A Python development company can create solutions for analyzing sentiments.
Why Sentiment Analysis is Critical?
In this day and age of world driven by social media networks, businesses rely really heavily on data and online reputations. Unstructured data comes from various sources like emails, chats, surveys, news articles, documents etc. Social media platforms like Twitter, Facebook, Instagram and others pose serious challenges, not just because of the enormous data generated, but also because of the language used to express sentiments that range from stickers, emojis to memes & chat abbreviations. They also use Python mobile development to build applications for Smartphones.
Sentiment analysis is of critical importance for professionals from the fields of marketing, advertising, economics, political science and other related fields that bank on human-computer interaction. Businesses that make sense out of the data are able to get insights from unstructured data to find gems of patterns and relationships related to buyers. There are several online listening and monitoring tools used to do sentiment analysis. Each of the tools has a widely varying degree of performance. When it comes to sentiment analysis, accuracy is of incredible importance. A Python web development company offers solutions using these tools for sentiment analysis.
Consider this example: “I’m craving a Starbucks Cappuccino badly.” Most of the systems will interpret this above statement as negative for the brand due to the use of word bad. Contextual understanding by the system is where the difference lies.
Case Study: Twitter Sentiment Analysis
How Python Can Help In Sentiment Analysis?
The syntax and build of Python applications resemble object-oriented languages like C, C++ & Java. The beginning of python application development for sentiment analysis was a great obstacle. However, it has improved drastically over the years. It can be simply used for custom data analysis tasks that are synced with a web application. Python is a comprehensive programming language and is used by a Python development company in India as a great tool to execute algorithms. Python backed VADER (Valence Aware Dictionary and sentiment Reasoner). offers great advantages in sentiment analysis.
It’s a versatile tool to analyze social media type text while being readily applicable to work on multiple domains
It doesn’t require training data
Live streaming data can be easily analyzed
It is not affected by speed-performance tradeoff.
The critical aspect of VADER sentiment analysis is that it is an open-source implementation in python. Contact us today for a FREE CONSULTATION Python Programming: Making Sense out of Sentiment Analysis
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