def _get_tweets_based_on_request(request):
search_term = request.GET.get('topic')
tweet_url = request.GET.get('tweet_url')
username = request.GET.get('user')
limit = int(request.GET.get('limit', 50))
if search_term:
tweets, error = data_fetch_public.get_tweets_from_search(
search_term, limit, data_fetch_constants.DATA_SOURCE_TWEEPY
)
return tweets
elif tweet_url:
try:
user, tweet_id = utils.get_user_tweet_id_from_tweet_url(tweet_url)
except:
return render(request, 'clientapp/error.html', {})
tweets, error = data_fetch_public.get_replies_of_tweet(
tweet_id, user, limit, data_fetch_constants.DATA_SOURCE_TWEEPY
)
return tweets
elif username:
tweets, error = data_fetch_public.get_tweets_of_user(
username, limit, data_fetch_constants.DATA_SOURCE_TWEEPY
)
return tweets
return None
def _get_tweets_from_user_scores(user_scores, limit):
all_tweets = []
it_count = 0
for username, score in user_scores:
it_count += 1
if it_count > MAX_DEPTH:
continue
# print('Getting data for: ', username)
tweets, error = data_fetch_public.get_tweets_of_user(
username, limit, data_fetch_constants.DATA_SOURCE_TWEEPY)
all_tweets.extend(tweets)
return all_tweets
def get_graph_for_user(user, limit=50):
tweets, error = data_fetch_public.get_tweets_of_user(
user, limit, data_fetch_constants.DATA_SOURCE_TWEEPY)
if error:
return []
summary = summarizer.get_results_summary(tweets, TOXICITY_THRESHOLD)
# print('Top mentions:', summary.top_mentioned_users)
all_tweets = tweets
all_tweets.extend(
_get_tweets_from_user_scores(summary.top_mentioned_users.items(),
limit))
# print('Top hashtags:', summary.top_hashtags)
all_tweets.extend(
_get_tweets_from_hashtag_scores(summary.top_hashtags.items(), limit))
return [
data_point for data_point in yield_data_points_from_tweets(all_tweets)
]
def summary(request):
search_term = request.GET.get('topic')
tweet_url = request.GET.get('tweet_url')
username = request.GET.get('user')
limit = int(request.GET.get('limit', 50))
error = False
tweets = []
about = None
analysis_type = TYPE_USER
if search_term:
tweets, error = data_fetch_public.get_tweets_from_search(
search_term, limit, data_fetch_constants.DATA_SOURCE_TWEEPY
)
about = 'Topic: %s' % search_term
analysis_type = TYPE_TOPIC
elif tweet_url:
try:
user, tweet_id = utils.get_user_tweet_id_from_tweet_url(tweet_url)
except:
return render(request, 'clientapp/error.html', {})
tweets, error = data_fetch_public.get_replies_of_tweet(
tweet_id, user, limit, data_fetch_constants.DATA_SOURCE_TWEEPY
)
about = 'User: %s; Tweet: %s' % (user, tweet_id)
analysis_type = TYPE_CONVERSATION
elif username:
tweets, error = data_fetch_public.get_tweets_of_user(
username, limit, data_fetch_constants.DATA_SOURCE_TWEEPY
)
about = 'User: %s' % username
analysis_type = TYPE_USER
else:
context = {
'homeresult': {
'top_trends': _get_top_trends_data(),
'top_searches': _get_top_searches_data(),
}
}
return render(request, 'clientapp/summary.html', context)
if error:
return render(request, 'clientapp/error.html', {})
return _render_results_with_summary(request, about, analysis_type, search_term, tweets)
def analyze_user(request):
user = request.GET.get('user')
user_clean = utils.get_clean_username(user)
tweets, error = data_fetch_public.get_tweets_of_user(
user_clean, 100, data_fetch_constants.DATA_SOURCE_TWEEPY
)
if error:
return JsonResponse({
'error': error
}, safe=False)
logger.info('Analyzing toxicity of results')
start = time.time()
result = [
tweet.to_dict()
for tweet in tweets
if tweet.user == user
]
end = time.time()
logger.info('Took ' + str(end - start) + ' seconds')
return JsonResponse(result, safe=False)