Parse hashtags from social media posts

Parsing hashtags from social media posts involves extracting words or phrases that are preceded by the # symbol. Here’s a breakdown of how to parse hashtags from a text string, followed by example code snippets in Python:

Approach:

• Identify all words prefixed with #

• Allow letters, numbers, and underscores in hashtags

• Ignore punctuation and special characters that are not part of hashtags

Example Python Code Using Regular Expressions:

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import re

def parse_hashtags(text):
    # Match hashtags: starts with # followed by alphanumerics or underscores
    hashtags = re.findall(r'#w+', text)
    return hashtags

Example Usage:

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post = "Loving the new features in #AI and #MachineLearning! #100DaysOfCode 🚀"
print(parse_hashtags(post))

Output:

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['#AI', '#MachineLearning', '#100DaysOfCode']

Extended Variant (without # symbol in output):

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def parse_hashtags(text):
    return [tag.lstrip('#') for tag in re.findall(r'#w+', text)]

Output:

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['AI', 'MachineLearning', '100DaysOfCode']

To Handle Unicode/International Hashtags (optional, if your platform supports):

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def parse_hashtags(text):
    return re.findall(r'#w+', text, flags=re.UNICODE)

Typical Use Cases:

• Content tagging and categorization

• Trending topic analysis

• Hashtag suggestion tools

• Sentiment or topic filtering

Let me know if you need the same logic implemented in another programming language.