def upload_tweet_sentiment():
print('Process started, it can take several time. Follow updates through ' \
'the log...')
dbm_local = DBManager(collection='tweets_esp_hpai')
dbm_remote = DBManager(collection='bsc-ls',
config_fn='config_mongo_hpai.json')
query = {'$and': [{'lang': {'$in': SPAIN_LANGUAGES}},
{'$or': [{'place.country': 'Spain'},
{'user.location': {'$in': \
get_spain_places_regex()}}]}]}
query.update({'retweeted_status': {'$exists': 0}})
query.update({'sentiment_score': {'$exists': 1}})
tweets = dbm_local.search(query)
total_tweets = tweets.count()
processing_counter = total_segs = modified_records = found_tweets = 0
logging.info('Going to upload {0:,} tweets'.format(total_tweets))
for tweet in tweets:
start_time = time.time()
processing_counter += 1
logging.info('[{0}/{1}] Processing tweet:\n{2}'.\
format(processing_counter, total_tweets, tweet['id']))
sentiment_dict = {
'sentiment': {
'score':
tweet['sentiment_score']
if tweet['sentiment_score_polyglot'] else None,
}
}
if tweet['sentiment_score_polyglot']:
sentiment_dict['sentiment']['raw_score_polyglot'] = \
tweet['sentiment_score_polyglot']
if 'sentiment_score_sentipy' in tweet:
sentiment_dict['sentiment']['raw_score_sentipy'] = \
tweet['sentiment_score_sentipy']
if 'sentiment_score_affin' in tweet:
sentiment_dict['sentiment']['raw_score_affin'] = \
tweet['sentiment_score_affin']
ret_update = dbm_remote.update_record({'id': int(tweet['id'])},
sentiment_dict)
if ret_update.matched_count == 0:
logging.info('Could not find in the remote server a tweet with ' \
'the id {}'.format(tweet['id']))
elif ret_update.matched_count == 1:
found_tweets += 1
if ret_update.modified_count == 0:
logging.info('Found tweet but did not update.')
elif ret_update.modified_count == 1:
modified_records += 1
logging.info('Remote tweet update with sentiment info!')
total_segs += calculate_remaining_execution_time(
start_time, total_segs, processing_counter, total_tweets)
logging.info('Total processed tweets: {0:,}\n'\
'Total found tweets in remote server: {1:,}\n'
'Total updated tweets in remote server: {2:,}\n'.\
format(total_tweets, found_tweets, modified_records))
print('Process finished!')
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, colletion=None):
if not None:
self.__dbm_tweets = DBManager(colletion)
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']
}
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'])
exists = user['exists'] if 'exists' in user.keys() else ''
self.__nodes.add(
tuple({
'screen_name': user['screen_name'],
'ff_ratio': u_ff_ratio,
'exists': exists
}.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'])
exists_iuser = iuser['exists'] if 'exists' in iuser.keys(
) else ''
self.__nodes.add(
tuple({
'screen_name': iuser['screen_name'],
'ff_ratio': i_ff_ratio
}.items()))
edge = {
'nodeA': {
'screen_name': user['screen_name'],
'ff_ratio': u_ff_ratio,
'exists': exists
},
'nodeB': {
'screen_name': interacted_user,
'ff_ratio': i_ff_ratio,
'exists': exists_iuser
},
'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': [{
'user.screen_name': screen_name
}, {
'retweeted_status.user.screen_name': screen_name
}, {
'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[1].joinpath(
'sna', 'gefx', file_name + '_' + today + '.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>NetworkAnalysis</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="2" title="ff_ratio" type="float"/>\n')
f.write('<attribute id="5" title="exists" 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="2" value="{0}"/>\n'.format(
node['ff_ratio']))
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