.gitignore

@@ -1,2 +1 @@
 .jupyter/
-env/

data/general_analysis_results.json

@@ -1 +0,0 @@
-{"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

@@ -1,55 +0,0 @@
-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)