How do you Analyse data from twitter?
Go to Analysis > Twitter > Analyze Tweets and select all twitter documents that you would like to include in your analysis. The results will be shown in a table, which includes information about the author and the tweet (for example, how often the tweet has been retweeted or the number of likes a tweet received).
Is NLP same as Sentiment Analysis?
Sentiment Analysis (also known as opinion mining or emotion AI) is a sub-field of NLP that tries to identify and extract opinions within a given text across blogs, reviews, social media, forums, news etc.
What is the difference between NLP and Sentiment Analysis?
In simple terms, when the input data is mostly available in a natural human language such as free-text then the procedure of processing the natural language is known as Natural Language Processing (NLP). Sentiment analysis is the process of unearthing or mining meaningful patterns from text data.
What is twitter data analysis?
Sentiment analysis refers to identifying as well as classifying the sentiments that are expressed in the text source. Tweets are often useful in generating a vast amount of sentiment data upon analysis. These data are useful in understanding the opinion of the people about a variety of topics.
How to perform a sentiment analysis of tweets?
The Sentiment Analysis is performed while the tweets are streaming from Twitter to the Apache Kafka cluster. The analysis is done using the textblob module in Python. Because the module does not work with the Dutch language, we used the following approach. First, we detect the language of the tweet.
Which Python modules are used for Twitter sentiment analysis?
Three primary Python modules were used, namely pykafka for the connection with the Apache Kafka cluster, tweepy for the connection with the Twitter Streaming API, and textblob for the sentiment analysis. The producer fetches tweets based on a specified list of keywords.
How do I upload my sentiment analysis data to monkeylearn?
MonkeyLearn offers three simple ways to upload: Batch Analysis: upload a CSV or Excel file for a new YouTube analysis. MonkeyLearn will process the data and provide a CSV download with your sentiment analysis results.
What kind of API do you use for sentiment analysis?
We will use out-of-the-box Sentiment Analysis API that is already offered for free by Microsoft Cognitive Services. According to Microsoft, the Sentiment Analysis API ” returns a numeric score between 0 and 1. Scores close to 1 indicate positive sentiment and scores close to 0 indicate negative sentiment.