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Home
Python 3
Fake vs Genuine Review Distribution

Fake vs Genuine Review Distribution

Fake vs Genuine Review Distribution
Code
Plot the Distribution
Explanation

Fake vs Genuine Review Distribution

Instead of analyzing all reviews together, it is useful to separate fake and genuine reviews to observe their distribution individually.

Code

fake_reviews = df[df['label'] == 1]
genuine_reviews = df[df['label'] == 0]
print("Fake Reviews:", len(fake_reviews))
print("Genuine Reviews:", len(genuine_reviews))

Plot the Distribution

plt.figure(figsize=(6,6))
plt.pie(
df['label'].value_counts(),
labels=['Genuine', 'Fake'],
autopct='%1.1f%%',
startangle=90
)
plt.title("Percentage of Fake and Genuine Reviews")
plt.show()

Explanation

The pie chart shows the proportion of fake and genuine reviews in the dataset.

If both classes occupy similar portions of the chart, the dataset is well-balanced.

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Fake vs Genuine Review Distribution

Contents

Fake vs Genuine Review Distribution

Code

Plot the Distribution

Explanation

Fake Review Detection System using Machine Learning

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