给用户推荐tag¶
In [1]:
import numpy as np
In [2]:
with open("/Users/Administrator/desktop/cjc/tweet0127.dat", 'rb') as f:
chunk = f.readlines()
In [7]:
len(chunk)
Out[7]:
11993
In [3]:
import csv
lines = csv.reader((line.replace('\x00','') for line in chunk[1:]), delimiter=',', quotechar='"')
users = [i[9] for i in lines] #users存储所有的用户名数据
In [4]:
lines = csv.reader((line.replace('\x00','') for line in chunk[1:]), delimiter=',', quotechar='"')
tweets =[i[2] for i in lines] #tweets里存储所有的推特文本数据
In [10]:
users[1]
Out[10]:
'OccupyManJose'
In [11]:
tweets[:3]
Out[11]:
["The 27 Republican Bills That Aren't About Jobs http://t.co/fhcVmqwR #ows #occupy #opdx", "For those interested in #FinancialFriday, the weekly bank march in San Jose, here's more info: http://t.co/cnKv1UJz #OO #OSJ #OSF #OWS", "The 27 Republican Bills That Aren't About Jobs http://t.co/cJnc1HT1 #ows #occupy #opdx"]
In [5]:
import twitter_text
In [6]:
#把tweet文本中的hashtag提取出来
hashtaglist=[]
exlist=[]
for i in range(0,11992):
tweet = tweets[i]
ex = twitter_text.Extractor(tweet)
hashtags = ex.extract_hashtags()
hashtaglist.append(hashtags)
i=i+1
In [15]:
hashtaglist[0]
Out[15]:
[u'ows', u'occupy', u'opdx']
In [7]:
dir(twitter_text)
Out[7]:
['Autolink', 'Extractor', 'HitHighlighter', 'TwitterText', 'Validation', '__builtins__', '__doc__', '__file__', '__name__', '__package__', '__path__', 'autolink', 'extractor', 'force_unicode', 'highlighter', 'regex', 'unicode', 'validation']
In [17]:
len(hashtaglist)
Out[17]:
11992
In [18]:
len(users)
Out[18]:
11992
构建一个{用户名：{tag：次数}}的字典¶
In [19]:
userss=list(set(users))#获得一个不重复的用户列表
In [14]:
len(userss)
Out[14]:
4758
In [20]:
#建立一个hash1列表，存放每个用户（不重复）发的所有推特tag
hash1=[]
for i in range(0,4758):
hash1.append([])
for j in range(0,11992):
if users[j]==userss[i]:
hash1[i]=hash1[i]+hashtaglist[j]
j=j+1
i=i+1
In [21]:
hash1[0]
Out[21]:
[u'War', u'Armageddon', u'USA', u'EndWar', u'OWS', u'Feudal', u'wealth', u'OWS']
In [22]:
#建立一个列表a存放用户的{tag：次数}数据
a=[]
for i in hash1:
c={}
for j in i:
c.update({j:i.count(j)})
a.append(c)
In [20]:
len(a)
Out[20]:
4758
In [21]:
a[0]
Out[21]:
{u'Armageddon': 1,
u'EndWar': 1,
u'Feudal': 1,
u'OWS': 2,
u'USA': 1,
u'War': 1,
u'wealth': 1}
In [23]:
#建立最终我们需要的字典hashdict
hashdict={}
for i in range(4758):
hashdict.update({userss[i]:a[i]})
In [24]:
len(hashdict)
Out[24]:
4758
In [25]:
hashdict['OccupyManJose']
Out[25]:
{u'FinancialFriday': 2,
u'OO': 1,
u'OPDX': 1,
u'OSF': 1,
u'OSJ': 2,
u'OWS': 2,
u'OccupySanJose': 2,
u'Solidarity': 1,
u'oo': 2,
u'osf': 1,
u'osj': 2,
u'ows': 2}
In [26]:
#定义相似性函数
import numpy as np
def sim_distance(prefs,tag1,tag2):
si={}
for item in prefs[tag1]:
if item in prefs[tag2]:
si[item]=1
if len(si)==0: return 0
sum_of_squares=np.sum([np.power(prefs[tag1][item]-prefs[tag2][item],2)
for item in prefs[tag1] if item in prefs[tag2]])
return 1/(1+np.sqrt(sum_of_squares) )
In [26]:
hashdict['dohlink']
Out[26]:
{u'occupy': 2, u'occupyportland': 1, u'opdx': 5, u'ows': 7, u'pdx': 1}
In [27]:
sim_distance(hashdict, 'OccupyManJose','dohlink')
Out[27]:
0.16666666666666666
In [28]:
# 定义相关性函数
def sim_pearson(prefs,p1,p2):
si={}
for item in prefs[p1]:
if item in prefs[p2]: si[item]=1
n=len(si)
if n==0: return 0
sum1=np.sum([prefs[p1][it] for it in si])
sum2=np.sum([prefs[p2][it] for it in si])
sum1Sq=np.sum([np.power(prefs[p1][it],2) for it in si])
sum2Sq=np.sum([np.power(prefs[p2][it],2) for it in si])
pSum=np.sum([prefs[p1][it]*prefs[p2][it] for it in si])
num=pSum-(sum1*sum2/n)
den=np.sqrt((sum1Sq-np.power(sum1,2)/n)*(sum2Sq-np.power(sum2,2)/n))
if den==0: return 0
return num/den
In [29]:
sim_pearson(hashdict, 'OccupyManJose','dohlink')
Out[29]:
0
In [30]:
#匹配函数
def topMatches(prefs,person,n=5,similarity=sim_pearson):
scores=[(similarity(prefs,person,other),other)
for other in prefs if other!=person]
scores.sort( )
scores.reverse( )
return scores[0:n]
In [31]:
topMatches(hashdict,'OccupyManJose',n=3)
Out[31]:
[(1.1547005383792517, 'msofia7'), (1.1547005383792517, 'HenryThorough'), (1.0327955589886444, 'idrobinhood')]
In [32]:
#翻转键值对
def transformPrefs(prefs):
result={}
for person in prefs:
for item in prefs[person]:
result.setdefault(item,{})
# Flip item and person
result[item][person]=prefs[person][item]
return result
hashdict2 = transformPrefs(hashdict)
In [33]:
topMatches(hashdict2,'ows')
D:\Anaconda\lib\site-packages\ipykernel\__main__.py:14: RuntimeWarning: overflow encountered in int_scalars D:\Anaconda\lib\site-packages\ipykernel\__main__.py:14: RuntimeWarning: invalid value encountered in sqrt
Out[33]:
[(1.1547005383792517, u'rush'), (1.1547005383792517, u'asamomorg'), (1.1547005383792517, u'Oil'), (1.0690449676496976, u'Chinese'), (1.044465935734187, u'drones')]
In [34]:
#定义tag的相似性函数
def calculateSimilarItems(prefs,n=20):
result={}
itemPrefs=transformPrefs(prefs)
c=0
for item in itemPrefs:
c+=1
if c%100==0:
print "%d / %d" % (c,len(itemPrefs))
scores=topMatches(itemPrefs,item,n=n,similarity=sim_distance)
result[item]=scores
return result
itemsim=calculateSimilarItems(hashdict)
itemsim
100 / 3570 200 / 3570 300 / 3570 400 / 3570 500 / 3570 600 / 3570 700 / 3570 800 / 3570 900 / 3570 1000 / 3570 1100 / 3570 1200 / 3570 1300 / 3570 1400 / 3570 1500 / 3570 1600 / 3570 1700 / 3570 1800 / 3570 1900 / 3570 2000 / 3570 2100 / 3570 2200 / 3570 2300 / 3570 2400 / 3570 2500 / 3570 2600 / 3570 2700 / 3570 2800 / 3570 2900 / 3570 3000 / 3570 3100 / 3570 3200 / 3570 3300 / 3570 3400 / 3570 3500 / 3570
Out[34]:
{u'WhoseWinning': [(1.0, u'OWS'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews'),
(0, u'youpeople'),
(0, u'youngfems'),
(0, u'youmightbeaterrorist'),
(0, u'youcut'),
(0, u'york'),
(0, u'yippiecafe'),
(0, u'yemen'),
(0, u'yay'),
(0, u'xtube'),
(0, u'wtop'),
(0, u'wtf'),
(0, u'wsj')],
u'Communism': [(1.0, u'unemployment'),
(1.0, u'sgp'),
(1.0, u'rs'),
(1.0, u'rnc'),
(1.0, u'occupy'),
(1.0, u'nationaldebt'),
(1.0, u'liberal'),
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(1.0, u'Obama'),
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(0.5, u'topprog'),
(0.5, u'ocra'),
(0.5, u'jobs'),
(0.5, u'debt')],
u'Bailed': [(1.0, u'Treasury'),
(1.0, u'Tahrir'),
(1.0, u'Syria'),
(1.0, u'Revolution'),
(1.0, u'Protest'),
(1.0, u'Massacre'),
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(1.0, u'ArabSpring'),
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(0.5, u'Occupy'),
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(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews'),
(0, u'youpeople')],
u'29E': [(1.0, u'Camps'),
(0.5, u'Vaeo'),
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(0.5, u'Occupy'),
(0.5, u'OWS'),
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(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews'),
(0, u'youpeople'),
(0, u'youngfems'),
(0, u'youmightbeaterrorist')],
u'Occupyboston': [(1.0, u'ows'),
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(1.0, u'oo'),
(1.0, u'occupylondon'),
(1.0, u'OccupyBoston'),
(1.0, u'OccupyAtlanta'),
(1.0, u'Boston'),
(0.5, u'occupy'),
(0.5, u'Occupy'),
(0.33333333333333331, u'RafidainBank'),
(0.33333333333333331, u'Occupylondon'),
(0.25, u'Occupylsx'),
(0.20000000000000001, u'OWS'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews')],
u'protest': [(1.0, u'workingpoor'),
(1.0, u'workers'),
(1.0, u'wallstreet'),
(1.0, u'university'),
(1.0, u'unions'),
(1.0, u'truthers'),
(1.0, u'teamsters'),
(1.0, u'realradical'),
(1.0, u'radical'),
(1.0, u'public'),
(1.0, u'onepercent'),
(1.0, u'occupyvancouver'),
(1.0, u'occupytruth'),
(1.0, u'occupytrust'),
(1.0, u'occupytime'),
(1.0, u'occupythis'),
(1.0, u'occupyok'),
(1.0, u'occupyfbi'),
(1.0, u'occupycia'),
(1.0, u'occupyboston')],
u'owsnyc': [(1.0, u'worldpeace'),
(1.0, u'tyranny'),
(1.0, u'topprog'),
(1.0, u'slaves2xorps'),
(1.0, u'sheeple'),
(1.0, u'science'),
(1.0, u'republicandebate'),
(1.0, u'policeState'),
(1.0, u'opflower'),
(1.0, u'occupyboston'),
(1.0, u'occupyUmass'),
(1.0, u'occupySF'),
(1.0, u'occupy'),
(1.0, u'lgbt'),
(1.0, u'health'),
(1.0, u'globalrEvolution'),
(1.0, u'freespeech'),
(1.0, u'evolve'),
(1.0, u'boycottHOLLYWOOD'),
(1.0, u'billofrights')],
u'occupycanada': [(1.0, u'uspoli'),
(1.0, u'radical'),
(1.0, u'ows'),
(1.0, u'nspoli'),
(1.0, u'halifax'),
(1.0, u'cdnpoli'),
(1.0, u'OccupyUSA'),
(1.0, u'OccupyNS'),
(1.0, u'OWS'),
(1.0, u'Newt'),
(1.0, u'Gingrich'),
(1.0, u'GOP'),
(1.0, u'D17'),
(1.0, u'Alinsky'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth')],
u'AGW': [(1.0, u'gop'),
(1.0, u'dnc'),
(1.0, u'NRA'),
(1.0, u'FF'),
(1.0, u'BailOutJesus'),
(0.5, u'TeaParty'),
(0.14285714285714285, u'tpot'),
(0.14285714285714285, u'tlot'),
(0.14285714285714285, u'tcot'),
(0.125, u'p2'),
(0.083333333333333329, u'ows'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews'),
(0, u'youpeople'),
(0, u'youngfems')],
u'NYC': [(1.0, u'venezuela'),
(1.0, u'unOccupyPalestine'),
(1.0, u'troika'),
(1.0, u'transparency'),
(1.0, u'refugees'),
(1.0, u'racism'),
(1.0, u'privatization'),
(1.0, u'osf'),
(1.0, u'oo'),
(1.0, u'odc'),
(1.0, u'occupynashville'),
(1.0, u'occupyLA'),
(1.0, u'occ'),
(1.0, u'netanyahu'),
(1.0, u'medicina'),
(1.0, u'g8'),
(1.0, u'empire'),
(1.0, u'drones'),
(1.0, u'douchebag'),
(1.0, u'c\xe1rceles')],
u'nwo': [(1.0, u'gop'),
(1.0, u'dems'),
(1.0, u'altmedia'),
(1.0, u'OWS'),
(0.5, u'propaganda'),
(0.5, u'occupyboston'),
(0.5, u'nypd'),
(0.5, u'fldebate'),
(0.5, u'drones'),
(0.41421356237309509, u'teaparty'),
(0.33333333333333331, u'twister'),
(0.33333333333333331, u'toct'),
(0.33333333333333331, u'tlot'),
(0.33333333333333331, u'teapparty'),
(0.33333333333333331, u'teapartty'),
(0.33333333333333331, u'ronpaul'),
(0.33333333333333331, u'occupyoakland'),
(0.33333333333333331, u'occupynyc'),
(0.33333333333333331, u'occupyla'),
(0.33333333333333331, u'occupydavis')],
u'Marines': [(1.0, u'usrevolution'),
(1.0, u'usdor'),
(1.0, u'topprog'),
(1.0, u'osyd'),
(1.0, u'oo'),
(1.0, u'omel'),
(1.0, u'olsx'),
(1.0, u'occupy'),
(1.0, u'nycga'),
(1.0, u'anonymous'),
(1.0, u'Razboiul'),
(1.0, u'ROMANIA'),
(1.0, u'PiataUniversitatii'),
(1.0, u'OccupyNY'),
(1.0, u'Design'),
(1.0, u'Bloomberg'),
(1.0, u'ACTA'),
(0.5, u'p2'),
(0.5, u'ows'),
(0.5, u'moveyourmoney')],
u'RadicalTransparency': [(1.0, u'viezescholen'),
(1.0, u'tyt'),
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(1.0, u'spanishrevolution'),
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(1.0, u'progressive'),
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(1.0, u'policebrutality'),
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(1.0, u'oumb'),
(1.0, u'ohb'),
(1.0, u'occupywallstreet'),
(1.0, u'occupyour'),
(1.0, u'occupynieuws'),
(1.0, u'occupymexico'),
(1.0, u'occupylondon')],
u'paris': [(1.0, u'sydney'),
(1.0, u'solidarity'),
(1.0, u'rome'),
(1.0, u'rock'),
(1.0, u'music'),
(1.0, u'friends'),
(1.0, u'europe'),
(1.0, u'beijing'),
(1.0, u'australia'),
(1.0, u'artist'),
(1.0, u'FF'),
(0.5, u'Reutlingen'),
(0.5, u'Remscheid'),
(0.5, u'Pforzheim'),
(0.5, u'Offenbach'),
(0.5, u'Bremerhaven'),
(0.5, u'Boltrop'),
(0.5, u'Bergedorp'),
(0.25, u'ows'),
(0, u'\xd1ew\xdf')],
u'Mitt': [(1.0, u'wiunion'),
(1.0, u'tpot'),
(1.0, u'topprog'),
(1.0, u'tlot'),
(1.0, u'ows'),
(1.0, u'occupy'),
(1.0, u'healthcare'),
(1.0, u'free'),
(1.0, u'This'),
(1.0, u'TeaParty'),
(1.0, u'Santorum'),
(1.0, u'Romney'),
(1.0, u'OccupyWallStreet'),
(1.0, u'OccupyUSA'),
(1.0, u'OccupyKoch'),
(1.0, u'OccupyDC'),
(1.0, u'Newt'),
(1.0, u'Mittens'),
(1.0, u'MTP'),
(1.0, u'GetMoneyOut')],
u'ChildrensVillage': [(1.0, u'homeless'),
(1.0, u'OccupyLove'),
(1.0, u'J28'),
(1.0, u'1of45children'),
(0.5, u'youth'),
(0.5, u'ows'),
(0.5, u'occupyoakland'),
(0.5, u'occupy'),
(0.5, u'movein'),
(0.5, u'foreclosure'),
(0.5, u'decolonize'),
(0.5, u'OccupyOakland'),
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(0.5, u'OWSWest'),
(0.5, u'OWS'),
(0.5, u'OO'),
(0.5, u'NDNZ'),
(0.5, u'Movein'),
(0.5, u'MoveIn'),
(0.5, u'LOVE')],
u'G8': [(1.0, u'yemen'),
(1.0, u'walkthewalk'),
(1.0, u'victories'),
(1.0, u'unonymous'),
(1.0, u'unemployment'),
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(1.0, u'resist'),
(1.0, u'politics'),
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u'NewYork': [(1.0, u'venezuela'),
(1.0, u'occupyLA'),
(1.0, u'medicina'),
(1.0, u'c\xe1rceles'),
(1.0, u'Texas'),
(1.0, u'SanFrancisco'),
(1.0, u'Occupynyc'),
(1.0, u'NYC'),
(1.0, u'LosAngeles'),
(1.0, u'Boston'),
(0.5, u'owsnyc'),
(0.5, u'occupySF'),
(0.5, u'Occupy'),
(0.5, u'Espa\xf1a'),
(0.5, u'Chile'),
(0.5, u'Argentina'),
(0.33333333333333331, u'M\xe9xico'),
(0.33333333333333331, u'FreeTheFive'),
(0.33333333333333331, u'Cuba'),
(0.25, u'OccupySF')],
u'ChessPieces': [(1.0, u'wtf'),
(1.0, u'pipa'),
(1.0, u'eea'),
(1.0, u'PrECISE'),
(1.0, u'Obama'),
(1.0, u'CitizensUnited'),
(1.0, u'CNNDebate'),
(0.5, u'sopa'),
(0.5, u'ndaa'),
(0.33333333333333331, u'ows'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews'),
(0, u'youpeople'),
(0, u'youngfems'),
(0, u'youmightbeaterrorist')],
u'bailout': [(1.0, u'wi'),
(1.0, u'usa'),
(1.0, u'unions'),
(1.0, u'trending'),
(1.0, u'taxes'),
(1.0, u'syria'),
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(1.0, u'occupybanks'),
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(1.0, u'democrats'),
(1.0, u'corruption'),
(1.0, u'commondreams'),
(1.0, u'bankrupt'),
(1.0, u'a99')],
u'Tahrir': [(1.0, u'wageslavery'),
(1.0, u'twittercensor'),
(1.0, u'transparency'),
(1.0, u'tahrir'),
(1.0, u'sonofabitch'),
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(1.0, u'sd'),
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u'pride': [(1.0, u'occupy'),
(1.0, u'Romney'),
(1.0, u'OWS'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
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u'AMERICA': [(1.0, u'USA'),
(1.0, u'TPOT'),
(1.0, u'TLOT'),
(1.0, u'TEAPARTY'),
(1.0, u'TCOT'),
(1.0, u'P2'),
(1.0, u'OWS'),
(1.0, u'ONEPEOPLE'),
(1.0, u'ONELOVE'),
(1.0, u'ONEHEART'),
(1.0, u'ONECOUNTRY'),
(1.0, u'NOH8'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews'),
(0, u'youpeople')],
u'acampadaparis': [(1.0, u'syntagma'),
(1.0, u'spanishrevolution'),
(1.0, u'solidarity'),
(1.0, u'occupyLSX'),
(1.0, u'globalrevolution'),
(1.0, u'OWS'),
(1.0, u'15m'),
(0.5, u'ows'),
(0.5, u'occupy'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews'),
(0, u'youpeople'),
(0, u'youngfems'),
(0, u'youmightbeaterrorist'),
(0, u'youcut')],
u'TheGrey': [(1.0, u'value'),
(1.0, u'teaparty'),
(1.0, u'society'),
(1.0, u'scripture'),
(1.0, u'quote'),
(1.0, u'occupydc'),
(1.0, u'moral'),
(1.0, u'kingdom'),
(1.0, u'kids'),
(1.0, u'future'),
(1.0, u'dreams'),
(1.0, u'Zionist'),
(1.0, u'WMU'),
(1.0, u'Vampire'),
(1.0, u'TylerPerry'),
(1.0, u'TwitterCensored'),
(1.0, u'TonyRobbins'),
(1.0, u'TomCruise'),
(1.0, u'Terrorist'),
(1.0, u'Teachers')],
u'Shalom': [(1.0, u'Peace'),
(1.0, u'OccupyLSX'),
(1.0, u'Israel'),
(1.0, u'Iran'),
(1.0, u'Anonymous'),
(0.5, u'OWS'),
(0, u'\xd1ew\xdf'),
(0, u'zoomit'),
(0, u'yup'),
(0, u'youworkfortheman'),
(0, u'youtube'),
(0, u'youth'),
(0, u'youranonnews'),
(0, u'youpeople'),
(0, u'youngfems'),
(0, u'youmightbeaterrorist'),
(0, u'youcut'),
(0, u'york'),
(0, u'yippiecafe'),
(0, u'yemen')],
u'OpEpoch': [(1.0, u'wageslavery'),
(1.0, u'unonymous'),
(1.0, u'the99percent'),
(1.0, u'the99'),
(1.0, u'teaparty'),
(1.0, u'tdot'),
(1.0, u'tcot'),
(1.0, u'sopa'),
(1.0, u'socialmedia'),
(1.0, u'policebrutality'),
(1.0, u'pUNkCr3w'),
(1.0, u'p21'),
(1.0, u'oumbraid'),
(1.0, u'oumb'),
(1.0, u'occupywallstreet'),
(1.0, u'occupyumass'),
(1.0, u'occupyoakland'),
(1.0, u'occupyiowa'),
(1.0, u'occupydsm'),
(1.0, u'occupychicago')],
...}
In [35]:
#定义推荐tag的函数
def getRecommendedItems(prefs,itemMatch,user):
userRatings=prefs[user]
scores={}
totalSim={}
for (item,rating) in userRatings.items( ):
for (similarity,item2) in itemMatch[item]:
if item2 in userRatings: continue
scores.setdefault(item2,0)
scores[item2]+=similarity*rating
totalSim.setdefault(item2,0)
totalSim[item2]+=similarity
rankings=[(score/totalSim[item],item) for item,score in scores.items( )]
rankings.sort( )
rankings.reverse( )
return rankings
getRecommendedItems(hashdict,itemsim,'OccupyManJose')
Out[35]:
[(2.0, u'zoomit'), (2.0, u'youranonnews'), (2.0, u'yippiecafe'), (2.0, u'yay'), (2.0, u'wtop'), (2.0, u'worldwide'), (2.0, u'worldrevolution'), (2.0, u'workersrights'), (2.0, u'word'), (2.0, u'woo'), (2.0, u'woccupy'), (2.0, u'wn'), (2.0, u'withnewt'), (2.0, u'withNewt'), (2.0, u'winning'), (2.0, u'wildlife'), (2.0, u'wikileaks'), (2.0, u'wellplayed'), (2.0, u'welfare'), (2.0, u'weeds'), (2.0, u'weare99'), (2.0, u'water'), (2.0, u'wallstreet'), (2.0, u'wakeupamerica'), (2.0, u'vvvpr'), (2.0, u'vt'), (2.0, u'voters'), (2.0, u'videoforchange'), (2.0, u'video4change'), (2.0, u'usimperialism'), (2.0, u'usdor'), (2.0, u'uncut'), (2.0, u'ul4p'), (2.0, u'tzm'), (2.0, u'tvp'), (2.0, u'truthnow'), (2.0, u'topprog'), (2.0, u'tcot'), (2.0, u'shutDowntheBanks'), (2.0, u'senate'), (2.0, u'resist'), (2.0, u'realradical'), (2.0, u'polisario'), (2.0, u'p21'), (2.0, u'ouk'), (2.0, u'otxx'), (2.0, u'osyd'), (2.0, u'osd'), (2.0, u'ophx'), (2.0, u'opesr'), (2.0, u'opdx'), (2.0, u'oomovein'), (2.0, u'ooTAC'), (2.0, u'omel'), (2.0, u'ogp'), (2.0, u'of'), (2.0, u'odc'), (2.0, u'ochi'), (2.0, u'occupywallstreet'), (2.0, u'occupyumb'), (2.0, u'occupyucdavis'), (2.0, u'occupytogether'), (2.0, u'occupysf'), (2.0, u'occupysacto'), (2.0, u'occupyromance'), (2.0, u'occupyraid'), (2.0, u'occupyoakland'), (2.0, u'occupynashville'), (2.0, u'occupymovement'), (2.0, u'occupykc'), (2.0, u'occupyhouston'), (2.0, u'occupydfw'), (2.0, u'occupydenver'), (2.0, u'occupydc'), (2.0, u'occupydallas'), (2.0, u'occupyca'), (2.0, u'occupyboston'), (2.0, u'occupyaustin'), (2.0, u'occupyEverything'), (2.0, u'occupy'), (2.0, u'oakmtg'), (2.0, u'oWS'), (2.0, u'nlg'), (2.0, u'londonlsx'), (2.0, u'j27'), (2.0, u'globalRevolution'), (2.0, u'giabo'), (2.0, u'freedom'), (2.0, u'anonops'), (2.0, u'OccupyTogether'), (2.0, u'OccupyLondon'), (1.75, u'youpeople'), (1.6666666666666667, u'unonymous'), (1.6666666666666667, u'texas'), (1.5, u'youth'), (1.5, u'youmightbeaterrorist'), (1.5, u'wirecall'), (1.5, u'wethepeople'), (1.5, u'usrevolution'), (1.5, u'theylive'), (1.5, u'tahrir'), (1.5, u'stopmonsanto'), (1.5, u'solidarity'), (1.5, u'ronpaul2012'), (1.5, u'revolution'), (1.5, u'raid'), (1.3333333333333333, u'yemen'), (1.3333333333333333, u'twitterBlackout'), (1.3333333333333333, u'turnoffyourTV'), (1.3333333333333333, u'syria'), (1.3333333333333333, u'sotu'), (1.3333333333333333, u'smwknd'), (1.25, u'unions'), (1.25, u'socialmedia'), (1.0, u'\xd1ew\xdf'), (1.0, u'wordpress'), (1.0, u'wiunion'), (1.0, u'wealth'), (1.0, u'wageslavery'), (1.0, u'viezescholen'), (1.0, u'victories'), (1.0, u'unity'), (1.0, u'unitedwestand'), (1.0, u'unifiedleft'), (1.0, u'unemployment'), (1.0, u'tyt'), (1.0, u'twittercensorship'), (1.0, u'twittercensor'), (1.0, u'twitter'), (1.0, u'tweetboat'), (1.0, u'trollrats'), (1.0, u'transparency'), (1.0, u'tpot'), (1.0, u'tlot'), (1.0, u'the99percent'), (1.0, u'teaparty'), (1.0, u'stribpol'), (1.0, u'streetmedic'), (1.0, u'streetart'), (1.0, u'stopacta'), (1.0, u'spanishrevolution'), (1.0, u'sopa'), (1.0, u'sonofabitch'), (1.0, u'socialjustice'), (1.0, u'sgp'), (1.0, u'sd'), (1.0, u'schoonmakers'), (1.0, u'sandiego'), (1.0, u'ronpaul'), (1.0, u'riaa'), (1.0, u'reoccupation'), (1.0, u'realtalk'), (1.0, u'quoteboat'), (1.0, u'progressive'), (1.0, u'politics'), (1.0, u'policebrutality')]
构建用户评论网络¶
In [8]:
#提取出@的用户
import re
tweet = u"RT @TheNewDeal: Dear Republicans, ALL YOUR ANCESTORS IMMIGRATED HERE.If You're Not a Native American Indian, Shut the Hell Up. #OWS #p2 #tcot"
RTpattern = r'''@(\w+)'''
for word in re.findall(RTpattern,tweet):
print word
TheNewDeal
In [9]:
#将有转发评论关系的用户分别存放在rtusers和usersss中
rtusers=[]
usersss=[]
for i in range(11992):
for word in re.findall(RTpattern,tweets[i]):
rtusers.append(word)
usersss.append(users[i])
i=i+1
In [11]:
rtusers[:5]
Out[11]:
['TheNewDeal', 'dissentmagazine', 'TheNewDeal', 'OccupyAustin', 'kennethlipp']
In [12]:
usersss[:5]
Out[12]:
['CoolR1a', 'symphily', 'Amy_Etkind', 'SilverJediShade', 'SilverJediShade']
In [10]:
link_author_dict = {}
for i in range(len(rtusers)):
link_author_dict[usersss[i]] =rtusers[i]
In [11]:
link_author_dict['CoolR1a']
Out[11]:
'TheNewDeal'
In [12]:
graph=[]
for i in range(len(rtusers)):
graph.append((usersss[i],rtusers[i]))
i=i+1
In [23]:
import networkx as nx
G = nx.DiGraph()
for x,y in graph:
if x != y:
G.add_edge(x,y)
In [14]:
nx.info(G)
Out[14]:
'Name: \nType: DiGraph\nNumber of nodes: 5333\nNumber of edges: 8247\nAverage in degree: 1.5464\nAverage out degree: 1.5464'
In [15]:
nx.average_degree_connectivity(G)
Out[15]:
{1: 36.94115680374457,
2: 26.805858987090367,
3: 33.733333333333334,
4: 25.55592105263158,
5: 22.165467625899282,
6: 20.78228228228228,
7: 19.266409266409266,
8: 15.262254901960784,
9: 19.11111111111111,
10: 15.58,
11: 16.54025974025974,
12: 13.25925925925926,
13: 17.46153846153846,
14: 11.627551020408163,
15: 14.985185185185186,
16: 10.86111111111111,
17: 9.784313725490197,
18: 10.712121212121213,
19: 8.151315789473685,
20: 26.925,
21: 11.412698412698413,
22: 13.902597402597403,
23: 2.6335403726708075,
24: 6.666666666666667,
25: 4.44,
26: 3.480769230769231,
27: 11.24074074074074,
28: 5.511904761904762,
29: 3.0258620689655173,
30: 6.355555555555555,
31: 19.129032258064516,
32: 26.072916666666668,
33: 15.242424242424242,
34: 17.08823529411765,
36: 6.430555555555555,
37: 1.6216216216216217,
38: 3.473684210526316,
39: 10.871794871794872,
40: 1.35,
41: 9.585365853658537,
43: 0.47674418604651164,
45: 15.777777777777779,
47: 24.23404255319149,
48: 5.416666666666667,
49: 14.857142857142858,
50: 11.02,
51: 10.72549019607843,
52: 1.4230769230769231,
53: 1.9811320754716981,
61: 13.737704918032787,
68: 3.088235294117647,
69: 9.985507246376812,
74: 0.10810810810810811,
79: 16.20253164556962,
92: 3.130434782608696,
98: 13.204081632653061,
103: 0.22330097087378642,
106: 0.0,
110: 14.6,
111: 0.05405405405405406,
133: 0.0,
157: 0.0,
171: 0.0,
356: 2.3230337078651684}
In [16]:
nx.average_neighbor_degree(G)
Out[16]:
{'Fesiconnection': 0.0,
'LaurenLaCapra': 0.0,
'wikinukes': 1.6666666666666667,
'fisheggtree': 0.0,
'StreamOfQubits': 0.0,
'greendoula': 1.0,
'DietCokeUS': 0.0,
'Dan4Liberty': 0.0,
'vizuality2': 0.0,
'lwats80': 2.0,
'OmaiBJeezus': 0.0,
'Samwise': 0.0,
'GaianCollective': 0.0,
'occupysebas': 0.0,
'occupycanada': 0.0,
'DakotaLeeC': 0.0,
'OccupyNewsthe99': 0.0,
'INGRID58NL': 0.0,
'coutpost': 0.0,
'trendwerks': 0.0,
'Justn_Thyme': 0.0,
'BlueRidgeData': 2.0,
'Polarspark': 0.0,
'Nigeriawhatsnew': 2.0,
'EvanRRoss': 0.0,
'maureen_murray': 3.0,
'NJWineGeek': 2.0,
'CivicAttitude': 4.375,
'wookietv': 0.0,
'MayorRTRybak': 0.0,
'HEILALALIU': 0.0,
'VCSP8': 2.5,
'TorianBrown': 0.0,
'AliGaudiosi': 10.666666666666666,
'WhyCoy': 0.0,
'DennisLane': 0.0,
'TravisJDawson': 4.0,
'LupeFiasco': 0.0,
'LukeBrinker': 1.0,
'bmoriarty2': 0.0,
'OccupyXXX': 0.0,
'newfiemedia': 6.0,
'NONOTAGAIN': 0.5,
'MegRobertson': 1.3333333333333333,
'johnsin': 3.0,
'TConspiracyChef': 0.0,
'symphily': 0.0,
'vanlenning': 4.0,
'psychonoetics': 0.0,
'occupykcbot': 0.0,
'hollyannbb': 1.0,
'AFLCIO': 0.0,
'LegionJJ': 0.5,
'ThinkAboutItYes': 0.0,
'Occupocalypse': 2.25,
'Oryx2046': 0.0,
'Fvash': 2.5,
'BHPanimalwatch': 0.0,
'billmaher': 0.0,
'KarlRove': 0.0,
'demandprogress': 0.0,
'thehill': 0.0,
'OpieRadio': 0.0,
'citizenschannel': 0.0,
'mdwwww': 0.0,
'apneac': 0.0,
'RichardBrodsky': 0.0,
'Eristophanes': 0.0,
'Jane_WI': 0.8333333333333334,
'JoeTheMailmanNJ': 0.0,
'Maerad1': 5.0,
'occupyAtlBot': 5.666666666666667,
'craftercar': 0.0,
'DougEDougie': 0.0,
'CitzMediaGuild': 2.0,
'ACLU': 0.0,
'Ustin93': 0.0,
'occupytampa': 0.0,
'mgroveau': 0.0,
'm_wonderful': 1.0,
'So1idarityMedia': 0.0,
'EnterGalactic_': 13.0,
'GeoSew': 1.0,
'citizensradio': 0.0,
'Pudingtane': 0.0,
'LivingLiesBlog': 0.0,
'OWSBuenosAires': 0.0,
'TCOTRetweet': 1.0,
'MoomjyN': 0.0,
'btnafas7oria': 0.0,
'globallady2': 0.0,
'queerninja': 2.0,
'newsmotion_org': 0.0,
'critmasspanic': 14.5,
'cheffy6c': 1.6666666666666667,
'RebelCapitalist': 0.0,
'OccamsTazer': 1.6666666666666667,
'occupyUMD': 0.0,
'andreaglorioso': 0.0,
'occupyUMB': 0.0,
'ajenglish': 0.0,
'vanschuppen': 1.5,
'gburge': 6.5,
'catskillprovs': 0.5,
'TheDudeInSF': 13.0,
'TPISCzar': 2.0,
'OccupyHouston': 0.0,
'jillstein2012': 0.0,
'UnaSpenser': 3.0,
'WeThinkPro': 0.0,
'SaraM0113': 6.25,
'sylviamagallan': 2.0,
'CemeteryMvmt': 0.0,
'luhvmoarnowXD': 8.2,
'nick_sibilla': 0.0,
'gbedard1': 0.0,
'kdarkmaul': 1.0,
'indivixen': 2.6666666666666665,
'JanetRWeil': 29.0,
'OmniusManifest3': 0.0,
'OmniusManifest2': 0.0,
'OmniusManifest1': 0.0,
'JeremySapienza': 11.0,
'dohlink': 0.0,
'whowhatwhy': 0.0,
'MariaTeresa1': 0.0,
'NexusIndivulsus': 0.0,
'PeoplesReport': 7.75,
'lleanaNYC': 0.0,
'DBillyP': 0.5,
'OccupyDC': 0.0,
'WhishaStar_': 0.0,
'ttipton1': 1.0,
'bobcat4evah': 1.0,
'FooteSteppes': 0.0,
'RealityDeviants': 5.222222222222222,
'RTPortland': 0.5,
'AC360': 0.0,
'1cpu4rent': 0.0,
'NYDNLemire': 0.0,
'OccupyWatcher': 6.0,
'Interdome': 0.0,
'mmmoonie': 0.0,
'JohnnyDee62': 2.0,
'KamalaHarris': 0.0,
'Joe99percent': 5.5,
'baseballcrank': 0.0,
'ProtestInTheUSA': 0.0,
'McBlondeLand': 0.0,
'OmniusManifesto': 0.0,
'dmwatts83': 0.5,
'Kidipede': 1.0,
'smlgjohn': 0.0,
'anon_thony': 13.5,
'OccupyBigBanks': 0.0,
'forbes': 0.0,
'eclecticbrotha': 0.0,
'ramonasvoices': 0.0,
'howtodoit1': 0.0,
'UWAGdotorg': 0.0,
'SolutionsTdy': 0.0,
'EricAtienza': 10.0,
'whimgrrl': 2.75,
'roamincat55': 2.0,
'GeneticLiberal': 0.0,
'flotsam_jetsum': 1.0,
'jesfacekillah': 1.5,
'Leeannmac77': 5.4,
'Joe_Covey': 0.0,
'johnkt09': 0.0,
'OccupySLO': 0.0,
'RoseBellitzia': 2.0,
'jlbrenner': 0.0,
'CapsCop': 0.0,
'balihai2': 3.1666666666666665,
'Yekbuns': 0.0,
'xsarahsays': 0.0,
'PersonalEscrito': 0.0,
'CREDOmobile': 0.0,
'RFromMN': 0.0,
'SamSeder': 0.0,
'vdHurk4congress': 11.333333333333334,
'johnvanderwal': 0.0,
'Chockycake51': 0.0,
'NancyPelosi': 0.0,
'CWAUnion': 0.0,
'Dick_Chavez': 1.0,
'nickmargerrison': 0.0,
'QuiteBahraini': 0.0,
'4Fashionmixxxx': 1.0,
'AFairGo': 0.0,
'occupynorfolk': 0.0,
'vanjones68': 0.0,
'grandmatojosie1': 0.0,
'CherieMortice': 0.0,
'GlobalVagabond_': 1.0,
'MikeElk': 1.0,
'ulma': 1.0,
'TGatlif': 27.0,
'greatdecider': 0.6666666666666666,
'NoJusticNoDonut': 12.0,
'BeLLShocK': 16.0,
'OccupyColleges': 1.5,
'215head': 0.0,
'WSJ': 0.0,
'Birdseye1': 0.0,
'Child_Support_': 3.888888888888889,
'mortymty': 0.0,
'rightanglerec': 10.0,
'helrond': 0.0,
'deanfx': 10.0,
'EviHef': 5.666666666666667,
'abujasim82': 0.0,
'Devilofabird': 1.0,
'mmargoshka': 9.0,
'rcalcina': 0.0,
'abzadous': 0.0,
'BiancaJagger': 0.0,
'ephemeralobject': 0.6666666666666666,
'polyglot84': 0.5,
'wayneradcliffe': 0.0,
'Perfect_Timing': 8.0,
'AlpYLCU': 0.0,
'OccupyTheG8': 0.0,
'dmcrane': 0.0,
'FoolishReporter': 8.6,
'LoLSmyleyFace': 0.0,
'tnr': 0.0,
'Greedsakiller': 0.75,
'n4cerinc': 0.0,
'JAMyerson': 0.0,
'cjohanns': 0.0,
'FUREE': 2.5,
'GreenPages': 0.0,
'nayrbgo': 0.0,
'StopTheCityRT': 0.0,
'enrique2009': 0.5,
'Agentmg17': 4.230769230769231,
'frankmillerink': 0.0,
'johnmagnumxxx': 1.0,
'lemonsandkiwi': 0.0,
'CitizenCohn': 1.0,
'MattWilliams06': 0.0,
'WaveFoundation': 1.6666666666666667,
'bsrds': 0.0,
'miaaculpa': 22.0,
'smwag': 0.0,
'MotormouthNews': 0.0,
'l0737373': 0.0,
'2JamesClark': 0.0,
'PoliticalSentry': 0.0,
'_girlalex': 4.285714285714286,
'RodyEKEN': 2.0,
'OleJerr': 0.0,
'Occupism': 0.0,
'BardOfEarth': 0.0,
'occupy_harvard': 0.0,
'sweetadelinevt': 19.0,
'newint': 0.0,
'GovPaterson710': 0.0,
'bitchasskiss': 3.0,
'lexisnexus': 0.0,
'emerhi': 0.0,
'GetUpStandUp2': 15.5,
'OpManning': 39.0,
'verveandspunk': 0.0,
'i_Govern': 0.0,
'ShantyTownie': 9.666666666666666,
'ZapataMty': 0.0,
'Az_iq': 0.0,
'tom_kuna': 0.0,
'murdockstwisted': 0.0,
'EWErickson': 0.0,
'NotaThreat2u': 2.0,
'WillAbERags': 10.333333333333334,
'jevetapp': 2.0,
'cielomiomarito': 0.0,
'yettakurland': 0.0,
'Nimphaea1': 13.5,
'gainer2420': 3.0,
'OccupyGTF_MT': 0.0,
'rkexperience': 13.5,
'Bokwe_Invest': 0.0,
'LGBTweet': 0.0,
'wrella': 13.5,
'David_EHG': 13.5,
'DouglasWilder': 2.0,
'Auriandra': 0.3333333333333333,
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...}
In [26]:
nx.closeness_centrality(G)
Out[26]:
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'Heart_and_Crown': 0.0,
'HeavenLeeOps': 0.0,
'agemmato': 0.00018754688672168043,
'deoxnard': 0.00018754688672168043,
'p0isAn0N': 0.00018754688672168043,
'justinhaaheim': 0.0,
'OCCUPYCARLISLE': 0.019003785695458613,
'viertlau000': 0.00018754688672168043,
'mdapore': 0.0003375843960990247,
'RevDannyFisher': 0.013908789110973804,
'Twittcensorship': 0.0,
'subverzo': 0.013486395616371341,
'OccupyTheEditor': 0.0,
'rawstory': 0.0,
'GuySoft': 0.0,
'ACMSinc': 0.00018754688672168043,
'SeizeDaMedia': 0.00037509377344336085,
'beaztbeatz': 0.01383524341427503,
'impoliteopinion': 0.00018754688672168043,
'RupertTurdcock': 0.00018754688672168043,
'bloomberg': 0.0,
'porsche4848': 0.0003375843960990247,
'HarrpyElephante': 0.0,
'ElonEch': 0.019275484518264142,
'anarchists': 0.0,
'AlmosJustice': 0.015455284078142537,
'harryallen': 0.0,
'RonPaul_2012': 0.0,
'sohailstyle': 0.00018754688672168043,
'FlippinUID': 0.0002500625156289072,
'Northern_Magpie': 0.0005626406601650412,
'alvaroLlobell': 0.010726815107138129,
'DTLAL': 0.00018754688672168043,
'HobbesDurden': 0.0006751687921980494,
'rebelpundit': 0.0,
'occupymandolin': 0.0,
'Nemisis69': 0.021148202861803748,
'unhaunting': 0.010772658652674794,
'kokobyrd': 0.011166932046756709,
'RageHour': 0.0,
'RockDocLV': 0.02262329465035314,
'the': 0.0,
'girlcop': 0.00037509377344336085,
'ianinegypt': 0.0,
'hubbabubba62': 0.0003375843960990247,
'PHX99percent': 0.01082245926445115,
'NationofChange': 0.0,
'nugoat': 0.00018754688672168043,
'thejoshuablog': 0.0003375843960990247,
'pndblog': 0.0,
'anon_pinko': 0.0,
'mslusus': 0.015253877769853987,
'Gonzo_Oin': 0.00018754688672168043,
'debradickerson': 0.013913139686235289,
'GenericNegro': 0.00018754688672168043,
'owsar': 0.02697796860908284,
'tinadupuy': 0.0,
'sistertoldjah': 0.00037509377344336085,
'B1n4ry_M4xX': 0.0,
'boothefam': 0.00018754688672168043,
'Carbon1953': 0.0,
'Amool_Sama': 0.00018754688672168043,
'OccupyProv': 0.015333272570479067,
...}
In [14]:
GU=G.to_undirected(reciprocal=True)
graphs = list(nx.connected_component_subgraphs(GU))
In [16]:
import numpy as np
size = []
for i in graphs:
size.append(len(i.nodes()))
len(size), np.max(size)
Out[16]:
(5204, 9)
In [36]:
gs = []
for i in graphs:
if len(i.nodes()) >3:
gs.append(i)
len(gs)
Out[36]:
12
In [37]:
for g in gs:
print len(g.nodes())
4 4 8 4 4 4 5 4 5 9 8 5
In [38]:
g_max = gs[0]
len(g_max.nodes())
Out[38]:
4
In [40]:
import matplotlib.pyplot as plt
pos = nx.spring_layout(G)
nx.draw(G,pos,with_labels=False,node_size = 5,node_color= 'lightblue' ,alpha=0.5, edge_color='grey')
plt.show()
In [43]:
import matplotlib
import matplotlib.pyplot as plt
matplotlib.rc("savefig", dpi=400)
pos = nx.spring_layout(G)
#定义一个布局，此处采用了spectral布局方式，后变还会介绍其它布局方式，注意图形上的区别
nx.draw(G,pos,with_labels=False,node_size = 5,node_color= 'lightblue' ,alpha=0.8, edge_color='grey')
#绘制规则图的图形，with_labels决定节点是非带标签（编号）,node_size是节点的直径
plt.show()
In [39]:
import matplotlib.pyplot as plt
pos = nx.spring_layout(g_max)
nx.draw(g_max,pos,with_labels=False,node_size = 20)
plt.show()
