Project At A Glance

Objective: Discover sentiments associated with posts in the 'Hot' section of r/worldnews and classify them as Positive, Negative and Neutral.

Data: 754x1 Dataset of the sub-reddit's headlines scraped using the Reddit API. [View Scraper Notebook] [Download]

Implementation: Reddit API, PRAW, NLTK's Sentiment Intensity Analyzer (SIA)

Results:

  • More than half of the headlines were classified as Neutral (~55%).
  • However, Negative Headlines (33%) still outweigh Positive Headlines (12%) by about 2.75x.
  • Dataset generated with labelled values to formulate models with better intelligence in the future.

Deployment: View this project on GitHub.

Dependencies 

import pandas as pd
from pprint import pprint

Dataset Initialization 

df = pd.read_csv('reddit-headlines.csv')

df.head()
Unnamed: 0 headlines
0 0 Mass graves dug in the besieged Ukrainian city...
1 1 British aircraft carrier leading massive fleet...
2 2 Spain detains $600 million yacht linked to Rus...
3 3 Photo shows officials taking down the Russian ...
4 4 Marina Ovsyannikova: Russian journalist tells ...

Using NLTK's Sentiment Intensity Analyzer 

import nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer as SIA

import matplotlib.pyplot as plt
import seaborn as sns

sia= SIA()
results = []

for line in df['headlines']:
    pol_score = sia.polarity_scores(line)
    pol_score['headline'] = line
    results.append(pol_score)
pprint(results[:3], width=100)

[{'compound': -0.7579,
  'headline': 'Mass graves dug in the besieged Ukrainian city of Mariupol, as locals bury their '
              'dead',
  'neg': 0.333,
  'neu': 0.667,
  'pos': 0.0},
 {'compound': 0.0,
  'headline': 'British aircraft carrier leading massive fleet off Norway',
  'neg': 0.0,
  'neu': 1.0,
  'pos': 0.0},
 {'compound': 0.0,
  'headline': 'Spain detains $600 million yacht linked to Russian oligarch: Reuters',
  'neg': 0.0,
  'neu': 1.0,
  'pos': 0.0}]

Generating DataFrame with Polarity Scores 

df = pd.DataFrame.from_records(results)

df.sample(4)
neg neu pos compound headline
380 0.506 0.494 0.000 -0.9231 Tigray war has seen up to half a million dead ...
22 0.289 0.711 0.000 -0.4291 'Why? Why? Why?' Ukraine's Mariupol descends i...
660 0.000 0.806 0.194 0.3400 Ukraine's 'hero' President Zelensky set to rec...
725 0.100 0.594 0.306 0.6705 There is no life for Ukrainian people: Boxing ...

Labelling and Classification 

df['label'] = 0
df.loc[df['compound']>0.33, 'label'] = 1
df.loc[df['compound']<-0.33, 'label'] = -1

df.sample(4)
neg neu pos compound headline label
461 0.273 0.727 0.000 -0.4588 Trudeau and almost every Canadian MP banned fr... -1
482 0.000 0.647 0.353 0.5994 Help yourself by helping us, Ukraine's Zelensk... 1
420 0.000 1.000 0.000 0.0000 Russia, India explore opening alternative paym... 0
748 0.239 0.761 0.000 -0.2960 Russia's state TV hit by stream of resignations 0 
df.label.value_counts()

 0    414
-1    247
 1     93
Name: label, dtype: int64
df.label.value_counts(normalize=True)*100 

 0    54.907162
-1    32.758621
 1    12.334218
Name: label, dtype: float64

Examples 

print('Positive Headlines:\n')
pprint(list(df[df['label'] == 1].headline)[:5], width=200)

print('\n\n Negative Headlines:\n')
pprint(list(df[df['label'] == -1].headline)[:5], width=200)

print('\n\n Neutral Headlines:\n')
pprint(list(df[df['label'] == 0].headline)[:5], width=200)

Positive Headlines:

['Tibetans seek justice after 63 years of uprising against Chinese rule',
 "The Ministry of Foreign Affairs on Tuesday (March 15) praised a Russian woman for her courage after she held up an anti-war sign on live Russian TV. MOFA head: 'It takes courage to be the voice of "
 "conscience'.",
 'Saudi Arabia considers accepting yuan for oil sales',
 'Russia and Ukraine looking for compromise in peace talks',
 'Turkmenistan leader’s son wins presidential election']


 Negative Headlines:

['Mass graves dug in the besieged Ukrainian city of Mariupol, as locals bury their dead',
 "Russia's former chief prosecutor says oligarch Roman Abramovich amassed his fortune through a 'fraudulent scheme'",
 'UN makes March 15 International Day to Combat Islamophobia',
 'Not violation of sanctions but Russian oil deal could put India on wrong side of history, says US',
 "'Why? Why? Why?' Ukraine's Mariupol descends into despair"]


 Neutral Headlines:

['British aircraft carrier leading massive fleet off Norway',
 'Spain detains $600 million yacht linked to Russian oligarch: Reuters',
 'Photo shows officials taking down the Russian flag after Putin gets the boot from Council of Europe',
 'Marina Ovsyannikova: Russian journalist tells of 14-hour interrogation',
 'China wary of being impacted by Russia sanctions: Foreign Minister']

Results and Visualization 

fig, ax = plt.subplots(figsize=(8,8))
counts = df.label.value_counts(normalize=True)*100

sns.barplot(x=counts.index, y=counts, ax=ax)
ax.set_xticklabels(['Negative', 'Neutral', 'Positive'])
ax.set_ylabel('Percentage')

plt.show()

Exporting Labelled Dataset as (.csv) 

df_export = df[['headline', 'label']]

df_export.sample(4)
headline label
399 EU 'Concerned' Over Disrupted Gas Supply, Shoo... 0
709 Woman fearing for family in Ukraine urges Cana... -1
618 New Zealand cuts fuel tax and halves public tr... -1
560 Slovakia meets NATO defence spending commitmen... 1 
df_export.to_csv('reddit-headlines-labelled.csv', encoding='utf-8', index=True)