Twitter offers interesting advantages such as the brevity of the tweets as well as its reactivity, moreover Twitter is open and the texts that are submitted are accessible to all thanks to a web service which facilitates the exploitation of the data. What do customers like about your company? What components are eliciting the most negative feedback? Simultaneously, Twitter sentiment analysis can give useful information for decision making. Twitter sentiment analysis helps you to monitor what people are saying about your product or service on social media and can assist you in detecting irate consumers or unfavorable remarks before they escalate. The extracted sentiments can then be used to generate statistics on the general feeling of a community. The objective of opinion mining is to analyze a large amount of data in order to deduce the different feelings expressed in it. This process appeared at the beginning of the 2000s and has become increasingly popular due to the abundance of data coming from social networks, especially those provided by Twitter. In natural language processing, opinion mining (also called sentiment analysis) is the analysis of feelings from dematerialized textual sources on large quantities of data (big data). Then, we will log these tweets along with their sentiments in an Airtable base. In order to do that, we will perform a sentiment analysis with Tinq.ai on the latest tweets that contain the Nike keyword. In this tutorial, we will learn how to analyze a twitter feed for a certain brand and understand what is being said about it.įor the sake of this tutorial, we want to know how people feel about Nike. One problem when it comes to analyzing tweets is that it has to be done in real time so that nothing is missed. ![]() This is a popular method for organizations to determine and categorize opinions about a product, service, or idea. ![]() Sentiment analysis is a Natural Language Processing technique that identifies the emotional tone behind a body of text. One of the best methods to do that is to use sentiment analysis. If your brand relies on social media such as Twitter to gauge what customers or the general public think of it, it is crucial to monitor those channels and react accordingly. In order to build a great product, it is important to understand what customers think and want.
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