def __init__(self, user, retweetFactor=None, impactFactor=None, mcFactor=None, TFIDFArray = None):
self._api = APISingleton.getInstance()
self.id = user.id
self.screen_name = user.screen_name
self.userObj = user
self.retweetFactor = retweetFactor
self.impactFactor = impactFactor
self.mcFactor = mcFactor
self.TFIDFArray = TFIDFArray
self.similarity = None
if retweetFactor == None:
self.retweetFactor = self.__calcRetweetFactor()
self.impactFactor = self.__calcImpactFactor()
self.TFIDFArray = self._calcTFIDF()
def __init__(self,
user,
retweetFactor=None,
impactFactor=None,
mcFactor=None,
TFIDFArray=None):
self._api = APISingleton.getInstance()
self.id = user.id
self.screen_name = user.screen_name
self.userObj = user
self.retweetFactor = retweetFactor
self.impactFactor = impactFactor
self.mcFactor = mcFactor
self.TFIDFArray = TFIDFArray
self.similarity = None
if retweetFactor == None:
self.retweetFactor = self.__calcRetweetFactor()
self.impactFactor = self.__calcImpactFactor()
self.TFIDFArray = self._calcTFIDF()
def getUsersToFollow(keyword, count=10, currentFriends=[]):
twitterApi = APISingleton.getInstance()
users = twitterApi.search_users(q=keyword, per_page=random.randint(20, 200), page=random.randint(1,10))
results = []
goodResults = []
for u in users:
try:
eUser = EvalUser.load(u)
results.append(eUser)
results += eUser.BFS(100, random_walk=True)
goodResults = [u for u in results if u.getImpactFactor()*u.getRetweetFactor() > 0.05 and u.getUserObj().id not in currentFriends]
print "Keyword=",keyword, "GoodResults#=",len(goodResults)
if len(goodResults) > count:
return goodResults
except Exception:
traceback.print_exc(sys.stdout)
pass
return goodResults
def loadFromTwitter(cls, userId, userObj=None):
if not userObj:
userObj = APISingleton.getInstance().get_user(user_id=userId)
ret = cls(userObj)
ret.save()
return ret
import sys
import traceback
sys.path.append("../lib/")
from tweeapi.IR import getTFIDFArray
from db import DBSingleton
import psycopg2.extras
import simplejson
from tweeapi import APISingleton
from tweeapi.utils import EvalUser
if __name__ == "__main__":
twitterApi = APISingleton.getInstance()
tweets = twitterApi.search(q=sys.argv[1].lower(),
rpp=100,
page=1,
force=True)
tweets = [t.text for t in tweets]
tfidfArray = getTFIDFArray(tweets)
db = DBSingleton.getInstance()
cur = db.cursor(cursor_factory=psycopg2.extras.DictCursor)
cur.execute(
"select * from users where retweet_factor > 0.2 and impact_factor > 0.2 limit 1000;"
)
results = []
for row in cur:
self.queue = queue
threading.Thread.__init__(self)
def run(self):
global results
while True:
user = self.queue.get()
try:
results.append(EvalUser.load(user))
except Exception:
traceback.print_exc(sys.stderr)
self.queue.task_done()
if __name__ == "__main__":
twitterApi = APISingleton.getInstance()
users = twitterApi.search_users(q=sys.argv[1], per_page=200)
results = []
queue = Queue.Queue()
for i in range(20):
t = EvalThread(queue)
t.setDaemon(True)
t.start()
for u in users:
queue.put(u)
queue.join()
results.sort()
results.reverse()
for i in results:
def loadFromTwitter(cls, userId, userObj = None):
if not userObj:
userObj = APISingleton.getInstance().get_user(user_id=userId)
ret = cls(userObj)
ret.save()
return ret