Page 264 - Ai_C10_Flipbook
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SECTION B (Subjective Type Questions)
Short answer type questions.
1. What is the functionality of Meaning Cloud in the context of NLP?
2. Why are No-code NLP platforms beneficial for non-technical users?
3. What do you understand by the term sentiment analysis?
4. Write about any two of the sentiment analysis method.
5. What are the steps to follow in the process of data exploration?
21 st Century #Technology Literacy
Skills
Lab
1. Create a PowerPoint presentation to explain the various applications of NLP. Make separate slides for
each application and use graphics to make them attractive.
2. Find some more chatbots from the internet and write your information in a MS word file using their logos
as well as working of each chatbot.
21 st Century #Technology Literacy
Skills
Lab
Sentiment Analysis for FIFA World Cup 2022 Tweets Using Orange Data Mining
The FIFA World Cup 2022 was one of the most talked-about sporting events globally, and social media
platforms, especially X (formerly Twitter), were filled with real-time reactions from fans, players, and critics.
Analysing these tweets provides insights into public opinion and sentiment surrounding the event. By
performing sentiment analysis, we can classify tweets as positive, neutral, or negative and understand how
different aspects of the World Cup were perceived.
Problem Statement
The objective is to analyse tweets related to the FIFA World Cup 2022 and classify them as positive,
neutral, or negative using machine learning techniques.
Dataset
The dataset used in this case study is the FIFA World Cup 2022 Tweets Dataset, which is available on
Kaggle. This dataset contains tweets related to the FIFA World Cup 2022 and provides valuable insights into
fans' reactions to the event.
Now, we classify tweets related to the FIFA World Cup 2022 into different sentiment categories using
the Orange Data Mining Tool.
Answers
Exercise (Section A) Theory
A. 1. b 2. c 3. c 4. b 5. b 6. b 7. a 8. b
B. 1. NLP 2. Voice assistants 3. keyword extraction 4. words and phrases
5. Conversational agent 6. Google Translate 7. captions 8. 0 and 1
C. 1. True 2. False 3. False 4. False 5. True 6. False 7. False 8. False
Exercise (Section A) Practical
1. c. 2. c. 3. b. 4. c. 5. b.
262 Artificial Intelligence Play (Ver 1.0)-X

