Adds script for general dataset anaylsis

data/general_analysis_results.json

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+{"hashtags": 267255, "mention": 71142, "url": 141594, "tweet_count": 151690, "num_police_accounts": 163, "date_first_tweet": "2020-10-27 09:29:13", "date_last_tweet": "2023-03-16 11:42:58", "day_diff": 870, "avg_post_hour": 11.156780275562001, "num_text_tokens": 3764759}

src/general_analysis.py

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+import pandas as pd
+from datetime import datetime
+import json
+
+general_analysis_dict = {}
+
+date_format_str = "%Y-%m-%d %H:%M:%S"
+
+tweets_all_combined = pd.read_csv("data/tweets_all_combined.csv")
+
+tweets_meta = pd.concat([pd.read_csv("data/entity_old.tsv", sep="\t"),
+                         pd.read_csv("data/tweets.csv")])
+
+meta_infos = tweets_meta["entity_type"].value_counts()
+hashtags = meta_infos["hashtag"]
+mention = meta_infos["mention"]
+url = meta_infos["url"]
+
+count_tweets = tweets_all_combined["tweet_id"].value_counts().shape[0]
+count_police_accounts = tweets_all_combined["user_id"].value_counts().shape[0]
+date_first_tweet = datetime.strptime(tweets_all_combined['created_at'].min(), date_format_str)
+date_last_tweet = datetime.strptime(tweets_all_combined['created_at'].max(), date_format_str)
+day_diff = (date_last_tweet-date_first_tweet).days
+
+
+def hr_func(ts):
+    return ts.hour
+
+
+tweets_all_combined["created_at"] = pd.to_datetime(
+    tweets_all_combined["created_at"])
+
+tweets_all_combined["created_hour"] = tweets_all_combined["created_at"].apply(hr_func)
+
+avg_post_hour = tweets_all_combined["created_hour"].mean()
+
+
+num_text_tokens = tweets_all_combined["tweet_text"].str.split().apply(len).sum()
+
+
+general_analysis_dict["hashtags"] = int(hashtags)
+general_analysis_dict["mention"] = int(mention)
+general_analysis_dict["url"] = int(url)
+general_analysis_dict["tweet_count"] = int(count_tweets)
+general_analysis_dict["num_police_accounts"] = int(count_police_accounts)
+general_analysis_dict["date_first_tweet"] = date_first_tweet.strftime(date_format_str)
+general_analysis_dict["date_last_tweet"] = date_last_tweet.strftime(date_format_str)
+general_analysis_dict["day_diff"] = int(day_diff)
+general_analysis_dict["avg_post_hour"] = float(avg_post_hour)
+general_analysis_dict["num_text_tokens"] = int(num_text_tokens)
+
+
+print("Writing general analysis json dump")
+with open("data/general_analysis_results.json", "w") as f:
+    json.dump(general_analysis_dict, f)