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## DATASET SOURCE: | ||
- https://www.kaggle.com/adiamaan/modi-speeches | ||
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## Dataset Description : | ||
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- ID | ||
- TITLE | ||
- URL | ||
- ARTICLE TEXT | ||
- IMAGES | ||
- PUBLISH INFO | ||
- TAGS | ||
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### Columns Droped are : | ||
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- URL | ||
- IMAGES | ||
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### Columns Created : | ||
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- YEAR | ||
- MONTH | ||
- Sentiments | ||
- Sentimental Score |
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Narendra Modi - Text Speeches Analysis/Dataset/modi_speeches.csv
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Narendra Modi - Text Speeches Analysis/Images/Most common words from speech.png
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# NAREDRA MODI TEXT SPEECH ANALYSIS | ||
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### Aim : This project is to analyze the speeches of Narendra Modi. | ||
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### Dataset : https://www.kaggle.com/adiamaan/modi-speeches | ||
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### Library used : | ||
- Pandas | ||
- Numpy | ||
- String | ||
- Matplotlib | ||
- Seaborn | ||
- Word cloud | ||
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### Visual plots : | ||
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- ![](/Narendra%20Modi%20-%20Text%20Speeches%20Analysis/Images/Most%20common%20Tags.png) | ||
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- ![](/Narendra%20Modi%20-%20Text%20Speeches%20Analysis/Images/Word%20cloud.png) | ||
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- ![](/Narendra%20Modi%20-%20Text%20Speeches%20Analysis/Images/Most%20common%20words%20from%20speech.png) | ||
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- ![](/Narendra%20Modi%20-%20Text%20Speeches%20Analysis/Images/Number%20of%20Speeches%20per%20Year.png) | ||
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- ![](/Narendra%20Modi%20-%20Text%20Speeches%20Analysis/Images/Number%20of%20Speeches%20per%20Month.png) | ||
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### Analysis : | ||
- Firstly, frequecy of most 30 popular tags are plotted on bar graph. We can clearly observe the important goals of the government which includes Good Governance, Infrastructural Development, Promoting Digital India Campaign and Other government scemes. | ||
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- Secondly, analysis his speech that what key words mostly he includes in his speeches. This shows that he includes India, Economy, People, World friends, Productional growth and Welfare like words. | ||
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- Thirdly, frquency of its speeeches over a years and months. This concludes that in 2019 due to general election the frquency of speeches goes above 300, which was highest of all 4 years (excluding 2022, we have less data of that particular year). | ||
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- Lastly, Analysis the sentimental score of speeches which all postive infact all are greater than 0.9 points. |
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Narendra Modi - Text Speeches Analysis/Models/narendra-modi-speech-analysis.ipynb
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matplotlib==3.5.2 | ||
numpy==1.19.2 | ||
pandas==1.4.3 | ||
nltk==3.8.1 | ||
seaborn==0.11.2 | ||
vaderSentiment |