Sentiment Analysis
The mixed opinions and thoughts never get to any conclusion. It's always difficult to obtain a final outcome on any topic, or on anyone; especially at times when people post their opinions on social media platforms like Facebook, Instagram, and Twitter.
Awards And Accreditation
200+
Worldwide Clients
500+
Successful Projects
150+
Team Members
17+
Years in Industry
Sentiment Analysis Problem
In Our ML/DL Software Model, We tried finding out a collective opinion of Twitter users on Elon Musk, CEO of Tesla & SpaceX. For this, we did tweet mining, scrapped tweets using a Python library, ‘tweepy’ to form a dataset of all tweets related to Elon Musk. Using Data Science frameworks, Machine Learning & Deep Learning algorithms, and Python language, we were able to understand the mindset of Twitter on Musk from their tweets. We systematically modeled the language of texts in their tweets using NLP (Natural Language Processing), analyzed the Twittersphere, obtained NLP data by scraping tweets only to classify the opinions of the masses.
Sentiment Analysis Solution
Finally, after determining the polarity of masses collectively, one can conclude that the so-called Alien on earth, Elon Musk is one of the most loved, respected, acknowledged, well-treated, inspirational personalities in the world, everywhere you go.
Sentiment Analysis Features
Emotion Detection: Our tool easily identifies emotions expressed in the tweets, such as happiness, sadness, anger, etc. This feature helps gauge the emotional sentiment conveyed in the opinions. Which proves beneficial for all businesses.
Real-Time Data Analytics: This tool provides you with complete real-time data that is the latest like the retweet count, reply count, timestamp, user influence records, etc. So one can use it to track real-time analytics on Twitter.
Named Entity Recognition Feature: Our tool is capable enough to extract the named entities such as people, organizations, and locations that are mentioned by the particular user or a business.
Sentiment Lexicon Features: Our tool can easily count sentiments using positive, negative, and neutral word counts. Analyzing all such word counts, it provides you with the overall sentiment score about the tweets done by different users for a particular personality or business.
Sentiment Analysis Result
Such software models can help you out in knowing reviews about your freshly launched online product/services. By understanding consumers’, customers’, clients’, and viewers’ opinions, a company can improve its business presence on the internet in a short time.“Know Opinions About Your Business Product/Services!”