class NetworkAnalyzer:
__dbm_tweets = None
__dbm_users = None
__dbm_networks = None
__network = None
__graph = None
__nodes = set()
__unknown_users = set()
__node_sizes = None
def __init__(self):
self.__dbm_tweets = DBManager('tweets')
self.__dbm_users = DBManager('users')
self.__dbm_networks = DBManager('networks')
self.__network = []
def __computer_ff_ratio(self, friends, followers):
if followers > 0 and friends > 0:
return friends / followers
else:
return 0
# Get interactions in of a given users
def get_in_interactions(self, user_screen_name):
# compute in interactions, meaning, interactions in which the user
# was mentioned, retweeted, quoted, replied
in_inter_query = {'interactions.' + user_screen_name: {'$exists': 1},
'screen_name': {'$ne': user_screen_name}}
n_users = self.__dbm_users.search(in_inter_query)
in_interactions_dict, in_rts, in_rps = {}, {}, {}
in_qts, in_mts = {}, {}
total_in_interactions = 0
total_in_retweets, total_in_replies = 0, 0
total_in_mentions, total_in_quotes = 0, 0
for n_user in n_users:
n_user_interactions = n_user['interactions']
for i_user, interactions in n_user_interactions.items():
if i_user == user_screen_name:
in_interactions_dict[n_user['screen_name']] = interactions['total']
total_in_interactions += interactions['total']
if 'retweets' in interactions.keys():
total_in_retweets += interactions['retweets']
in_rts[n_user['screen_name']] = interactions['retweets']
if 'replies' in interactions.keys():
total_in_replies += interactions['replies']
in_rps[n_user['screen_name']] = interactions['replies']
if 'mentions' in interactions.keys():
total_in_mentions += interactions['mentions']
in_mts[n_user['screen_name']] = interactions['mentions']
if 'quotes' in interactions.keys():
total_in_quotes += interactions['quotes']
in_qts[n_user['screen_name']] = interactions['quotes']
in_interactions_obj = {
'total': {
'count': total_in_interactions,
'details': in_interactions_dict
},
'replies': {
'count': total_in_replies,
'details': in_rps
},
'retweets': {
'count': total_in_retweets,
'details': in_rts
},
'mentions': {
'count': total_in_mentions,
'details': in_mts
},
'quotes': {
'count': total_in_quotes,
'details': in_qts
}
}
user_dict = {
'in_interactions': in_interactions_obj
}
return user_dict
# Get interactions out of a given users
def get_out_interactions(self, user_screen_name):
user = self.__dbm_users.search({'screen_name': user_screen_name})[0]
# compute out interactions, meaning, interactions originated by
# the user
user_interactions = user['interactions']
out_interactions_dict, out_rts = {}, {}
out_rps, out_qts, out_mts = {}, {}, {}
total_out_interactions, total_out_retweets = 0, 0
total_out_mentions, total_out_replies = 0, 0
total_out_quotes = 0
for recipient, interactions in user_interactions.items():
out_interactions_dict[recipient] = interactions['total']
total_out_interactions += interactions['total']
if 'retweets' in interactions:
total_out_retweets += interactions['retweets']
out_rts[recipient] = interactions['retweets']
if 'replies' in interactions:
total_out_replies += interactions['replies']
out_rps[recipient] = interactions['replies']
if 'mentions' in interactions:
total_out_mentions += interactions['mentions']
out_mts[recipient] = interactions['mentions']
if 'quotes' in interactions:
total_out_quotes += interactions['quotes']
out_qts[recipient] = interactions['quotes']
out_interactions_obj = {
'total': {
'count': total_out_interactions,
'details': out_interactions_dict
},
'replies': {
'count': total_out_replies,
'details': out_rps
},
'retweets': {
'count': total_out_retweets,
'details': out_rts
},
'mentions': {
'count': total_out_mentions,
'details': out_mts
},
'quotes': {
'count': total_out_quotes,
'details': out_qts
}
}
# compile all information in a dictionary
user_dict = {
'out_interactions': out_interactions_obj
}
return user_dict
def create_users_db(self, clear_collection=False):
logging.info('::. Network Analyzer: Creating database of users, it can take several minutes, please wait_')
if clear_collection:
self.__dbm_users.clear_collection()
users = self.__dbm_tweets.get_unique_users()
users_count = len(users)
logging.info('::. Network Analyzer: Extracted {0} unique users from the database...'.format(users_count))
progress = 1
for user in users:
db_user = {
'screen_name': user['screen_name'],
'friends': user['friends'],
'followers': user['followers'],
'ff_ratio': self.__computer_ff_ratio(user['friends'], user['followers']),
'interactions': user['interactions'],
'tweets': user['tweets_count'],
'original_tweets': user['original_count'],
'rts': user['retweets_count'],
'qts': user['quotes_count'],
'rps': user['replies_count'],
'verified': user['verified']
}
# Assign the party and movement to the party and movement that are more related to the user
# counting both Hashtags and Mentions by the user
user_parties = self.__dbm_tweets.get_party_user(user['screen_name'])
user_parties_count = len(user_parties) or 0
logging.debug('::. Network Analyzer: User {0} has {1} associated parties...'
.format(user['screen_name'],user_parties_count))
if user_parties_count > 0:
user_party = user_parties[0]
db_user.update({'most_interacted_party': user_party['partido']})
user_movements = self.__dbm_tweets.get_movement_user(user['screen_name'])
user_movements_count = len(user_movements) or 0
logging.debug('::. Network Analyzer: User {0} has {1} associated movements...'
.format(user['screen_name'], user_movements_count))
if user_movements_count > 0:
user_movement = user_movements[0]
db_user.update({'most_interacted_movement': user_movement['movimiento']})
else:
db_user.update({'most_interacted_movement': ''})
else:
db_user.update({'most_interacted_party': '', 'movement': ''})
# Assign the party and movement to the party and movement that are more related to the user
# counting both Hashtags and Mentions by the user
upp = UserPoliticalPreference()
user_party = upp.get_user_political_party(user['screen_name'])
user_movement = upp.get_user_political_movement(user['screen_name'])
db_user.update({'party': user_party, 'movement': user_movement})
filter_query = {'screen_name': user['screen_name']}
logging.debug('::. Network Analyzer: Updating/creating user {0} ({1}/{2})...'
.format(user['screen_name'], progress, users_count))
progress += 1
self.__dbm_users.update_record(filter_query, db_user, create_if_doesnt_exist=True)
def generate_network(self, subnet_query={}, depth=1, file_name='network', override_net=False):
net_query = subnet_query.copy()
net_query.update({'depth': depth})
ret_net = self.__dbm_networks.search(net_query)
# the net doesn't exist yet, let's create it
if ret_net.count() == 0 or override_net:
logging.info('Generating the network, it can take several minutes, please wait_')
users = self.__dbm_users.search(subnet_query)
# for each user generate his/her edges
for user in users:
if 'ff_ratio' in user.keys():
u_ff_ratio = user['ff_ratio']
else:
u_ff_ratio = self.__computer_ff_ratio(user['friends'], user['followers'])
pbb_score = user['bot_analysis']['pbb'] if 'bot_analysis' in user.keys() else ''
self.__nodes.add(tuple({'screen_name': user['screen_name'], 'party': user['party'],
'movement': user['movement'], 'ff_ratio': u_ff_ratio,
'pbb': pbb_score}.items()))
for interacted_user, interactions in user['interactions'].items():
iuser = self.__dbm_users.find_record({'screen_name': interacted_user})
if not iuser:
if depth > 1:
iuser_ffratio = self.__get_ffratio(interacted_user)
if not iuser_ffratio:
self.__unknown_users.add(interacted_user)
continue
else:
self.__unknown_users.add(interacted_user)
continue
else:
if 'ff_ratio' in iuser.keys():
i_ff_ratio = iuser['ff_ratio']
else:
i_ff_ratio = self.__computer_ff_ratio(iuser['friends'], iuser['followers'])
pbb_iuser_score = user['bot_analysis']['pbb'] if 'bot_analysis' in iuser.keys() else ''
self.__nodes.add(tuple({'screen_name': iuser['screen_name'], 'party': iuser['party'],
'movement': iuser['movement'], 'ff_ratio': i_ff_ratio,
'pbb': pbb_iuser_score}.items()))
edge = {
'nodeA': {'screen_name': user['screen_name'], 'ff_ratio': u_ff_ratio,
'party': user['party'], 'movement': user['movement'],
'pbb': pbb_score},
'nodeB': {'screen_name': interacted_user, 'ff_ratio': i_ff_ratio,
'party': iuser['party'], 'movement': iuser['movement'],
'pbb': pbb_iuser_score},
'weight': interactions['total']
}
self.__network.append(edge)
logging.info('Created a network of {0} nodes and {1} edges'.format(len(self.__nodes), len(self.__network)))
logging.info('Unknown users {0}'.format(len(self.__unknown_users)))
# save the net in a gefx file for posterior usage
f_name = self.save_network_in_gexf_format(file_name)
logging.info('Saved the network in the file {0}'.format(f_name))
db_net = {'file_name': str(f_name)}
db_net.update(net_query)
self.__dbm_networks.save_record(db_net)
else:
f_net = ret_net[0]
logging.info('The network was already generated, please find it at {0}'.format(f_net['file_name']))
def create_graph(self):
logging.info('Creating the graph, please wait_')
self.__graph = net.DiGraph()
ff_ratio = defaultdict(lambda: 0.0)
# create a directed graph from the edge data and populate a dictionary
# with the friends/followers ratio
for edge in self.__network:
user = edge['nodeA']['screen_name']
interacted_with = edge['nodeB']['screen_name']
num_interactions = edge['weight']
u_ff_ratio = edge['nodeA']['ff_ratio']
self.__graph.add_edge(user, interacted_with, weight=int(num_interactions))
ff_ratio[user] = float(u_ff_ratio)
# obtain central node
# degrees = net.degree(self.__graph)
# central_node, max_degree = sorted(degrees, key=itemgetter(1))[-1]
# center the graph around the central node
# ego_graph = net.DiGraph(net.ego_graph(self.__graph, central_node))
return
def get_graph_nodes(self):
return len(self.__nodes)
def get_graph_edges(self):
return len(self.__network)
def get_graph(self):
return self.__graph
def get_node_sizes(self):
return self.__node_sizes
def __get_ffratio(self, screen_name):
query = {
'$or': [
{'tweet_obj.user.screen_name': screen_name},
{'tweet_obj.retweeted_status.user.screen_name': screen_name},
{'tweet_obj.quoted_status.user.screen_name': screen_name}
]
}
tweet_obj = self.__dbm_tweets.find_record(query)
if tweet_obj:
tweet = tweet_obj['tweet_obj']
if 'retweeted_status' in tweet.keys():
return self.__computer_ff_ratio(tweet['retweeted_status']['user']['friends_count'],
tweet['retweeted_status']['user']['followers_count'])
elif 'quoted_status' in tweet.keys():
return self.__computer_ff_ratio(tweet['quoted_status']['user']['friends_count'],
tweet['quoted_status']['user']['followers_count'])
else:
return self.__computer_ff_ratio(tweet['user']['friends_count'],
tweet['user']['followers_count'])
else:
return None
def save_network_in_gexf_format(self, file_name):
today = datetime.strftime(datetime.now(), '%m/%d/%y')
f_name = pathlib.Path(__file__).parents[2].joinpath('sna', 'gefx', file_name+'.gexf')
with open(str(f_name), 'w', encoding='utf-8') as f:
f.write('<?xml version="1.0" encoding="UTF-8"?>\n')
f.write('<gexf xmlns="http://www.gexf.net/1.2draft" xmlns:viz="http://www.gexf.net/1.1draft/viz" '
'xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" '
'xsi:schemaLocation="http://www.gexf.net/1.2draft http://www.gexf.net/1.2draft/gexf.xsd" '
'version="1.2">\n')
f.write('<meta lastmodifieddate="{0}">\n'.format(today))
f.write('<creator>PoliticBots</creator>\n')
f.write('<description>{0}</description>\n'.format(file_name))
f.write('</meta>\n')
f.write('<graph mode="static" defaultedgetype="directed">\n')
# add data attributes
f.write('<attributes class="node">\n')
f.write('<attribute id="0" title="party" type="string"/>\n')
f.write('<attribute id="1" title="movement" type="string"/>\n')
f.write('<attribute id="2" title="ff_ratio" type="float"/>\n')
f.write('<attribute id="3" title="pbb" type="float"/>\n')
f.write('</attributes>\n')
# add nodes
f.write('<nodes>\n')
node_id = 0
list_nodes = []
for node_tup in self.__nodes:
node = dict(node_tup)
f.write('<node id="{0}" label="{1}">\n'.format(node_id, node['screen_name']))
f.write('<attvalues>\n')
f.write('<attvalue for="0" value="{0}"/>\n'.format(node['party']))
f.write('<attvalue for="1" value="{0}"/>\n'.format(node['movement']))
f.write('<attvalue for="2" value="{0}"/>\n'.format(node['ff_ratio']))
f.write('<attvalue for="3" value="{0}"/>\n'.format(node['pbb']))
f.write('</attvalues>\n')
#f.write('<viz:size value="{0}"/>\n'.format(node['ff_ratio']))
f.write('</node>\n')
node_id += 1
list_nodes.append(node['screen_name'])
f.write('</nodes>\n')
# add edges
f.write('<edges>\n')
edge_id = 0
for edge in list(self.__network):
id_vertexA = list_nodes.index(edge['nodeA']['screen_name'])
id_vertexB = list_nodes.index(edge['nodeB']['screen_name'])
weight = edge['weight']
f.write('<edge id="{0}" source="{1}" target="{2}" weight="{3}"/>\n'.format(edge_id, id_vertexA,
id_vertexB, weight))
edge_id += 1
f.write('</edges>\n')
f.write('</graph>\n')
f.write('</gexf>\n')
return f_name
class UserPoliticalPreference:
db_tweets, db_users = None, None
def __init__(self):
self.db_tweets = DBManager('tweets')
self.db_users = DBManager('users')
self.hashtags, self.metadata = self.__get_hashtags_and_metadata()
def __get_hashtags_and_metadata(self):
script_parent_dir = pathlib.Path(__file__).parents[1]
config_fn = script_parent_dir.joinpath('config.json')
configuration = get_config(config_fn)
keywords, metadata = parse_metadata(configuration['metadata'])
hashtags = []
for keyword in keywords:
if '@' not in keyword:
# The following hashtags are excluded because they are proper names of
# movements and people
if keyword not in ['HonorColorado', 'ColoradoAñetete', 'tuma']:
hashtags.append(keyword.lower())
return hashtags, metadata
def __get_tweet_hashtags(self, tweet_obj):
tweet_hashtags = []
if 'entities' in tweet_obj.keys():
for hashtag in tweet_obj['entities']['hashtags']:
tweet_hashtags.append(hashtag['text'])
return tweet_hashtags
def __get_hashtag_metadata(self, hashtag):
for metadata in self.metadata:
if metadata['keyword'].lower() == hashtag.lower():
return metadata
def get_user_political_movement(self, user_screen_name):
user_movement = None
user_political_preference = defaultdict(int)
filter = {
'relevante': {
'$eq': 1
},
'tweet_obj.user.screen_name': {
'$eq': user_screen_name
}
}
results = self.db_tweets.search(filter)
for tweet in results:
tweet_obj = tweet['tweet_obj']
if 'retweeted_status' in tweet_obj.keys():
tweet_hashtags = self.__get_tweet_hashtags(
tweet_obj['retweeted_status'])
else:
tweet_hashtags = self.__get_tweet_hashtags(tweet_obj)
for hashtag in tweet_hashtags:
if hashtag.lower() in self.hashtags:
hashtag_metadata = self.__get_hashtag_metadata(hashtag)
if hashtag_metadata['movimiento']:
user_political_preference[
hashtag_metadata['movimiento']] += 1
if user_political_preference:
s_user_political_preference = [
k for k in sorted(user_political_preference.items(),
key=lambda k_v: k_v[1],
reverse=True)
]
user_movement = s_user_political_preference[0][0]
return user_movement
def get_user_political_party(self, user_screen_name):
user_party = None
user_political_preference = defaultdict(int)
filter = {
'relevante': {
'$eq': 1
},
'tweet_obj.user.screen_name': {
'$eq': user_screen_name
}
}
results = self.db_tweets.search(filter)
for tweet in results:
tweet_obj = tweet['tweet_obj']
if 'retweeted_status' in tweet_obj.keys():
tweet_hashtags = self.__get_tweet_hashtags(
tweet_obj['retweeted_status'])
else:
tweet_hashtags = self.__get_tweet_hashtags(tweet_obj)
for hashtag in tweet_hashtags:
if hashtag.lower() in self.hashtags:
hashtag_metadata = self.__get_hashtag_metadata(hashtag)
if hashtag_metadata['partido_politico']:
user_political_preference[
hashtag_metadata['partido_politico']] += 1
if user_political_preference:
s_user_political_preference = [
k for k in sorted(user_political_preference.items(),
key=lambda k_v: k_v[1],
reverse=True)
]
user_party = s_user_political_preference[0][0]
return user_party
def update_users_political_preference(self, include_movement=True):
users = self.db_users.search({})
total_users = users.count()
users_counter = 0
for user in users:
users_counter += 1
user_movement, user_party = None, None
logging.info('Processing {0}/{1} users'.format(
users_counter, total_users))
if include_movement:
user_movement = self.get_user_political_movement(
user['screen_name'])
user_party = self.get_user_political_party(user['screen_name'])
logging.info('User {0} demonstrates to support {1}, {2}'.format(
user['screen_name'], user_party, user_movement))
self.db_users.update_record({'screen_name': user['screen_name']}, {
'party': user_party,
'movement': user_movement
})
def update_user_most_interacted_party_movement(self,
include_movement=True):
users = self.db_users.search({})
total_users = users.count()
users_counter = 0
for user in users:
users_counter += 1
user_most_interacted_movement, user_most_interacted_party = None, None
logging.info('Processing {0}/{1} users'.format(
users_counter, total_users))
if include_movement:
user_interacted_movements = self.db_tweets.get_movement_user(
user['screen_name'])
if len(user_interacted_movements) > 0:
user_most_interacted_movement = user_interacted_movements[
0]['movimiento']
user_interacted_parties = self.db_tweets.get_party_user(
user['screen_name'])
if len(user_interacted_parties) > 0:
user_most_interacted_party = user_interacted_parties[0][
'partido']
self.db_users.update_record(
{'screen_name': user['screen_name']}, {
'most_interacted_party': user_most_interacted_party,
'most_interacted_movement': user_most_interacted_movement
})
def update_tweet_user_political_preference(self, include_movement=True):
tweets = self.db_tweets.search({})
tweet_authors = defaultdict(dict)
total_tweets = tweets.count()
tweet_counter = 0
for tweet in tweets:
tweet_counter += 1
logging.info('Processing {0}/{1} tweets'.format(
tweet_counter, total_tweets))
tweet_obj = tweet['tweet_obj']
new_fields = {}
if tweet_obj['user']['screen_name'] not in tweet_authors.keys():
user = self.db_users.search(
{'screen_name': tweet_obj['user']['screen_name']})
try:
new_fields['author_party'] = user[0]['party']
except IndexError:
new_fields['author_party'] = None
if include_movement:
try:
new_fields.update(
{'author_movement': user[0]['movement']})
except IndexError:
new_fields.update({'author_movement': None})
tweet_authors[tweet_obj['user']['screen_name']] = new_fields
else:
new_fields = tweet_authors[tweet_obj['user']['screen_name']]
self.db_tweets.update_record(
{'tweet_obj.id_str': tweet_obj['id_str']}, new_fields)
def update_tweet_user_pbb(self):
tweets = self.db_tweets.search({})
tweet_authors = defaultdict(dict)
total_tweets = tweets.count()
tweet_counter = 0
for tweet in tweets:
tweet_counter += 1
logging.info('Processing {0}/{1} tweets'.format(
tweet_counter, total_tweets))
tweet_obj = tweet['tweet_obj']
new_fields = {}
if tweet_obj['user']['screen_name'] not in tweet_authors.keys():
user = self.db_users.search(
{'screen_name': tweet_obj['user']['screen_name']})
try:
new_fields['author_pbb'] = user[0]['bot_analysis']['pbb']
except IndexError:
new_fields['author_party'] = -1
tweet_authors[tweet_obj['user']['screen_name']] = new_fields
else:
new_fields = tweet_authors[tweet_obj['user']['screen_name']]
self.db_tweets.update_record(
{'tweet_obj.id_str': tweet_obj['id_str']}, new_fields)