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2024 Indian election sentimental analysis #63

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Akshat111111 opened this issue May 12, 2024 · 10 comments · Fixed by #231
Closed

2024 Indian election sentimental analysis #63

Akshat111111 opened this issue May 12, 2024 · 10 comments · Fixed by #231

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@Akshat111111
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The task is to find the sentiments and corelation with financial market movement.

@apooyadv
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Assign this to me.I'll use rnns for it.

@diptarup794
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Hi! I have previous experience working with nlp . Please assign this issue to me @Akshat111111

@tejasvinigoel
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Im interested in this, kindly assign it to me

@Akshat111111
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I have assigned you all.Firstly clarify your idea/approach so that there should not be any overlapping of work.

@apooyadv
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Could you please describe it a little more?

@Akshat111111
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Could you please describe it a little more?

You can simultaneously plot the sentiment of common people with the plot of nifty.Also both the things should be present in the same plot.

@milliondreamsblog
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milliondreamsblog commented May 12, 2024

Approch -
Sentiment Analysis:
Using transformer-based models like BERT or DistilBERT(because its lite on space) for sentiment analysis.
Fine-tuning these models on Indian political news articles and Twitter posts .
Utilizing a 5-point rating scale (very good, good, moderate, bad, very bad) can provide granularity in sentiment analysis, which can be helpful for market analysis.

Analyzing financial market movements could use time series analysis techniques - ARIMA (frankly, I don't know this part yet).

Finally, correlation analysis to identify any relationships between sentiment and market movements with techniques such as the Pearson correlation coefficient

Please assign me as well would love learn and contribute.

@Akshat111111
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Approch - Sentiment Analysis: Using transformer-based models like BERT or DistilBERT(because its lite on space) for sentiment analysis. Fine-tuning these models on Indian political news articles and Twitter posts . Utilizing a 5-point rating scale (very good, good, moderate, bad, very bad) can provide granularity in sentiment analysis, which can be helpful for market analysis.

Analyzing financial market movements, could use time series analysis techniques - ARIMA(fanckly idk this part yet)

finally , correlation analysis to identify any relationships between sentiment and market movements with techniques such as Pearson correlation coefficient.

Please assign me as well would love learn and contribute.

yeah your idea is good, so I will suggest you to create a new issue specifying your model name and start working on it

@milliondreamsblog
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hey I have created a new issue , issue has not being assigned tag of gssoc24

@Akshat111111
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Which issue ??

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5 participants