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scmvESP.py
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scmvESP.py
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import sys, os, newt, argparse, datetime, csv, random,unicodedata
import networkx as nx
import newtx as nwx
import urllib
#to do
#when doing eg hashtag search, need to be able to use original tagger list with differet filter arg
# ie print a 'try this' command to cope with different filter val. Requires new code block?
# triangulate: given list of N users, find folk who follow M of them
def checkDir(dirpath):
if not os.path.exists(dirpath):
os.makedirs(dirpath)
def report(m):
newt.report(m,True)
api=newt.getTwitterAPI()
#----------------------------------------------------------------
#user settings
#Examples:
## python scmvESP.py -filterfile reports/scmvESP/scmvESP_2011-12-17-20-38-50 -indegree 5 -outdegree 30 -outdegreemax 500
#python scmvESP.py -searchterm allotment veg OR fruit OR garden -tagsample 500 -outdegree 50 -indegree 20 -projection forward -typ friends -tagfilter 1
## python scmvESP.py -user tetley_teafolk -sample 5000 -mindegree 500
## python scmvESP.py -user tetley_teafolk -sample 200 -indegree 20 -outdegree 30
## python scmvESP.py -hashtag philately -tagsample 500 -tagfilter 5 -mindegree 20
## python scmvESP.py -searchterm philately -tagsample 500 -tagfilter 5 -mindegree 20
## python scmvESP.py -hashtag sherlock -tagsample 1500 -mindegree 75 -projection forward
## python scmvESP.py -searchterm http://www.johnwatsonblog.co.uk/ -tagsample 500 -tagfilter 1 -mindegree 20 -projection forward
# python scmvESP.py -fromfile ../users.txt -indegree 15 -outdegree 1 -projection forward
# python scmvESP.py -fromfile ../users.txt -indegree 15 -outdegree 1 -projection forward -filter 10
# python scmvESP.py -list emercoleman/cstwitter -indegree 15 -outdegree 1 -projection forward
#python scmvESP.py -users actiononhearing deafaction deafnessuk hearinglink -filter 2 -sample 500 -typ followers -outdegree 10 -indegree 10
#python scmvESP.py -searchterm anti bullying -tagsample 500 -tagfilter 1 -outdegree 20 -indegree 20 -projection forward -fname anti_bullying -location milton keynes -dist 500 -fname geoMK500_anti_bulliying
parser = argparse.ArgumentParser(description='Generate social positioning map')
parser.add_argument('-fname',default='scmvESP',help='Custom folder name')
group = parser.add_mutually_exclusive_group()
group.add_argument('-user',help='Name of a user (without the @) for whom you want to generate their ESP.')
group.add_argument('-users',nargs='*', help="A space separated list of usernames (without the @) for whom you want to generate their common ESP.")
group.add_argument('-fromfile',help='Name of a simple text file from which to enter a list of usernames (without the @) for whom you want to generate their common ESP.')
group.add_argument('-filterfile',help='Run a network filter on a project file.')
group.add_argument('-list',help='Grab users from a list. Provide source as: username/listname #IN TESTING')
group.add_argument('-lists',nargs='*',help='Grab users from a list. Provide source as: username/listname #IN TESTING')
#NOTE - the newt hashtag code allows us to exclude RTs; at the moment, the default to not exclude hashtaggers is used;
## TODO add in an argument to allow this to be controlled
group.add_argument('-hashtag',help='Hashtag for which you want to identify recent users and then generate their common ESP.')
group.add_argument('-searchterm',nargs='*',help='Searchterm for which you want to identify recent users and then generate their common ESP.')
parser.add_argument('-location',nargs='*',help="Search location")
parser.add_argument('-dist',type=float,help='Location search distance')
parser.add_argument('-typ',default='followers',help='Are we going to generate ESP from friends or followers?')
parser.add_argument('-typ2',default='friends',help='This relates to the second, projection step of the ESP process, and describes whether we project friends or followers of the folk identified by typ')
parser.add_argument('-sample',default=197,type=int,metavar='N',help='Sample the friends/followers (user, users); use 0 if you want all (users/users).')
parser.add_argument('-sample2',default=-1,type=int,metavar='N',help='Sample the friends/followers (user, users) for forward projection')
parser.add_argument('-tagsample',default=500,type=int,metavar='N',help='For hashtag/searchterm sample, number of recently hashtagged/search term including tweets to search for (hashtag,searchterm)')
parser.add_argument('-tagfilter',default=2,type=int,metavar='N',help='For hashtag or searchterm sample, number times a person needs to use tag/searchterm to count')
parser.add_argument('-filter',default=0,type=int,metavar='N',help='For use with users argument. Specify how many users the fr/fo must follow to be included as positioning sources.')
parser.add_argument('-projection',default='default',help='If you just want to find the innerfriends of friends/followers, and not the projection, set this false.')
parser.add_argument('-halt',help='Halt after innerfriends.')
#At the moment, mindegree dominates indegree and outdegree. Need to set exclusion rules accordingly
parser.add_argument('-mindegree',type=int,metavar='N',help='If you want to generate a labelled projection graph, set the minimum degree that nodes in the projection graph must have.')
#parser.add_argument('-maxdegree',type=int,metavar='N',help='If you want to generate a labelled projection graph, set the maximum degree that nodes in the projection graph must have.')
parser.add_argument('-indegree',type=int,metavar='N',help='If you want to generate a labelled projection graph, set the minimum in_degree that nodes in the ESP set and not in the projection set must have.')
parser.add_argument('-indegreemax',type=int,metavar='N',help='If you want to generate a labelled projection graph, set the maximum in_degree that nodes in the ESP set and not in the projection set must have.')
parser.add_argument('-outdegree',type=int,metavar='N',help='If you want to generate a labelled projection graph, set the minimum out_degree that nodes in the projection set must have.')
parser.add_argument('-outdegreemax',type=int,metavar='N',help='If you want to generate a labelled projection graph, set the maxiumum out_degree that nodes in the projection set must have.')
args=parser.parse_args()
#----------------------------------------------------------------
def logger(fname,args):
flog=open("reports/scmvESP/logger.csv","a")
logger=csv.writer(flog)
logger.writerow([fname,repr(args)])
flog.close()
def ascii(s):
if s!=None: return "".join(i for i in s if ord(i)<128)
else: return ''
def getTimeStampedProjDirName(path,stub):
now = datetime.datetime.now()
ts = now.strftime("_%Y-%m-%d-%H-%M-%S")
return path+'/'+stub+ts
def nowTime():
now = datetime.datetime.now()
ts = now.strftime("_%Y-%m-%d-%H-%M-%S")
return ts
checkDir('reports')
checkDir('reports/scmvESP')
fpf=''
def getSearchtermUsers(searchterm,num,limit,projname,location='',dist=''):
if location!='': term='locterm'
else: term='term'
return getGenericSearchUsers(searchterm,num,limit,projname,term,location,dist)
def getHashtagUsers(tag,num,limit,projname):
return getGenericSearchUsers(tag,num,limit,projname,"tag")
def getGenericSearchUsers(tag,num,limit,projname,styp="tag",location='',dist=''):
tweeters={}
tags={}
if styp=='tag':
print 'Looking for twitterers and tags in context of hashtag',tag
tweeters,tags,tweets=newt.twSearchHashtag(tweeters,tags,num, tag,exclRT=False)
elif styp=='locterm':
tweeters,tags,tweets=newt.twSearchNear(tweeters,tags,num, location, tag, dist=float(dist),exclRT=False)
else: #styp=='term'
print 'Looking for twitterers and tags in context of searchterm',tag
tweeters,tags,tweets=newt.twSearchTerm(tweeters,tags,num, tag,exclRT=False)
#newt.report_hashtagsearch('searchterm-'+qtag,tweeters,tags)
fo=open(projname+'/tweets.txt','wb+')
writer=csv.writer(fo)
for tweet in tweets:
writer.writerow([tweet['from_user_id'],tweet['from_user'],tweet['text'].encode('ascii','ignore'),tweet['to_user_id'],tweet['created_at']])
fo.close()
fo=open(projname+'/tweeps.txt','wb+')
writer=csv.writer(fo)
for tweeter in tweeters:
writer.writerow([tweeter])
fo.close()
fo=open(projname+'/cotags.txt','wb+')
writer=csv.writer(fo)
for cotag in tags:
writer.writerow([cotag])
fo.close()
for t in sorted(tags, key=tags.get, reverse=True):
print t,tags[t]
alltweeps=[]
tw=[]
tws={}
for i in tweeters:
alltweeps.append(i)
tws[i]=tweeters[i]['count']
if tws[i]>=limit:
tw.append(i)
print alltweeps
#this is a fudge; return alltweeps as well tw? Also generalis w/ getSourceList?
return tw
#--- http://stackoverflow.com/questions/312443/how-do-you-split-a-list-into-evenly-sized-chunks-in-python
def chunks(l, n):
""" Yield successive n-sized chunks from l.
"""
for i in xrange(0, len(l), n):
yield l[i:i+n]
#---
def getSourceList(users,typ,sampleSize,filterN):
tw={}
twc={}
twDetails={}
print users
#we can look up a max of 100 users...
#TO DO / HACK just sample 100 for now, if required...?
#if len(users)>100:
# users=random.sample(users, 500)
# print 'HACK FUDGE, only using 500 users:',users
if len(users)>100:
twd=[]
#print 'users',users
for l in chunks(users,100):
#print 'partial',l
tmp=api.lookup_users(screen_names=l)
twd.append(tmp)
else:
twd=api.lookup_users(screen_names=users)
for u in twd:
if type(u) is newt.tweepy.models.User:
twc[u.screen_name]=filterN
twDetails[u.screen_name]=u
fn=projname+'/userdetails.csv'
writer=csv.writer(open(fn,'wb+'),quoting=csv.QUOTE_ALL)
k=[ 'source','screen_name','name','description','location','time_zone','created_at','contributors_enabled','url','listed_count','friends_count','followers_count','statuses_count','favourites_count','id_str','id','verified','utc_offset','profile_image_url','protected']
writer.writerow(k)
for uu in twDetails:
u=twDetails[uu]
ux=['']
for x in [u.screen_name,u.name,u.description,u.location,u.time_zone]:
if x != None:
ux.append(unicodedata.normalize('NFKD', unicode(x)).encode('ascii','ignore'))
else: ux.append('')
for x in [u.created_at,u.contributors_enabled,u.url,u.listed_count,u.friends_count,u.followers_count,u.statuses_count,u.favourites_count,u.id_str,u.id,u.verified,u.utc_offset,u.profile_image_url,u.protected]:
ux.append(x)
try:
writer.writerow(ux)
except: pass
if sampleSize==0: sampleSize='all'
for user in users:
print "Getting ",typ," of ",user
if typ=="followers":
tmp=newt.getTwitterFollowersDetailsByIDs(api,user,sampleSize)
else:
tmp=newt.getTwitterFriendsDetailsByIDs(api,user,sampleSize)
print "Grabbed ",str(len(tmp)),typ,' for ',user
#tw.extend(tmp)
for t in tmp:
if t in twc:
twc[t]=twc[t]+1
else:
twc[t]=1
twDetails[t]=tmp[t]
#deDupeList=list(set(origList))
#deDupeList=filter(lambda e: e not in origList,origList)
for t in twc:
if twc[t]>=filterN: tw[t]=twDetails[t]
return tw
def getFriendsProjection(tw={},maxf=5000):
newt.gephiOutputFileByName(api,projname+'/'+args.typ+'_innerfriends.gdf', tw,maxf=maxf)
newt.gephiOutputFileByName(api,projname+'/'+args.typ+'_extrafriends.gdf', tw,'extrafriends',maxf=maxf)
newt.gephiOutputFileByName(api,projname+'/'+args.typ+'_outerfriends.gdf', tw,'outerfriends',maxf=maxf)
def getFollowersProjection(tw={},maxf=5000):
newt.gephiOutputFileByName(api,projname+'/'+args.typ+'_innerfollowers.gdf', tw,'followers',maxf=maxf)
newt.gephiOutputFileByName(api,projname+'/'+args.typ+'_extrafollowers.gdf', tw,'extrafollowers',maxf=maxf)
newt.gephiOutputFileByName(api,projname+'/'+args.typ+'_outerfollowers.gdf', tw,'outerfollowers',maxf=maxf)
def getFriendsView(tw={},maxf=5000):
newt.gephiOutputFileByName(api,projname+'/innerfriends.gdf', tw,maxf=maxf)
newt.gephiOutputFileByName(api,projname+'/extrafriends.gdf', tw,'extrafriends',maxf=maxf)
newt.gephiOutputFileByName(api,projname+'/outerfriends.gdf', tw,'outerfriends',maxf=maxf)
def getFollowersView(tw={},maxf=5000):
newt.gephiOutputFileByName(api,projname+'/innerfollowers.gdf', tw,'followers',maxf=maxf)
newt.gephiOutputFileByName(api,projname+'/extrafollowers.gdf', tw,'extrafollowers',maxf=maxf)
newt.gephiOutputFileByName(api,projname+'/outerfollowers.gdf', tw,'outerfollowers',maxf=maxf)
def labelGraph(LG,idlist):
idlabels=newt.twDetailsFromIds(api,idlist)
#There is going to be a clash on this filename:-(
f=open(projname+'/idnames.txt','wb+')
cf=csv.writer(f)
cf.writerow(['id','username','desc'])
for id in idlabels:
if str(id) in LG.node:
LG.node[str(id)]['label']=idlabels[id].screen_name
LG.node[str(id)]['fo_count']=idlabels[id].followers_count
LG.node[str(id)]['fr_count']=idlabels[id].friends_count
LG.node[str(id)]['updates']=idlabels[id].statuses_count
desc=idlabels[id].description
if desc !=None:
desc=desc.encode('ascii','ignore')
#LG.node[str(id)]['descr']=desc
#print LG.node[str(id)]['desc']
cf.writerow([id,idlabels[id].screen_name,desc])
LG.node[str(id)]['indegree']=LG.in_degree(str(id))
if idlabels[id].followers_count>0:
LG.node[str(id)]['fo_prop']=1.0*LG.in_degree(str(id))/idlabels[id].followers_count
else:
LG.node[str(id)]['fo_prop']=0.0
#LG.node[str(id)]['since']=idlabels[id].created_at
'''
LG.node[str(id)]['location']=idlabels[id].location
LG.node[str(id)]['desc']=idlabels[id].description
'''
LG.node[str(id)]['desc']=ascii(idlabels[id].description)
#print LG.node[str(id)]
f.close()
return LG
def filterNet(DG,mindegree,indegree,outdegree,outdegreemax,typ,addUserFriendships,user,indegreemax):
print 'In filterNet'
#need to tweak this to allow filtering by in and out degree?
if addUserFriendships==1:
DG=addFocus(DG,user,typ)
#handle min,in,out degree
filter=[]
#filter=[n for n in DG if DG.degree(n)>=mindegree]
for n in DG:
if outdegreemax==None or DG.out_degree(n)<=outdegreemax:
if mindegree!=None:
if DG.degree(n)>=mindegree:
filter.append(n)
else:
if indegree!=None:
if DG.in_degree(n)>=indegree:
filter.append(n)
if outdegree!=None:
if DG.out_degree(n)>=outdegree:
filter.append(n)
#the filter represents the intersect of the *degreesets
#indegree and outdegree values are ignored if mindegree is set
filter=set(filter)
H=DG.subgraph(filter)
#Superstitiously, perhaps, make sure we only grab nodes that project edges...
filter= [n for n in H if H.degree(n)>0]
L=H.subgraph(filter)
print "Filter set:",filter
print L.order(),L.size()
L=labelGraph(L,filter)
if mindegree==None: tm='X'
else: tm=str(mindegree)
if indegree==None: ti='X'
else: ti=str(indegree)
if outdegree==None: to='X'
else: to=str(outdegree)
if outdegreemax==None: tom='X'
else: tom=str(outdegreemax)
st='/'.join([projname,typ+'degree_'+tm+'_'+ti+'_'+to+'_'+tom+"_esp"])
nx.write_graphml(L, st+".graphml")
nx.write_edgelist(L, st+".txt",data=False)
fpf=st+'.graphml'
return fpf
'''
#delimiter=''
#indegree=sorted(nx.indegree(DG).values(),reverse=True)
indegree=H.in_degree()
outdegree=H.out_degree()
inout = [indegree, outdegree]
inoutpair = {}
for k in indegree.iterkeys():
inoutpair[k] = tuple(inoutpair[k] for inoutpair in inout)
fig = plt.figure()
ax = fig.add_subplot(111)
#ax.plot(indegree,outdegree, 'o')
#ax.set_title('Indegree vs outdegree')
degree_sequence=sorted(indegree.values(),reverse=True)
plt.loglog(degree_sequence)
plt.savefig( '/'.join([path,agent,typ,tt+"degree"+str(mindegree)+"outdegree_histogram.png"]))
#plt.show()
'''
def addFocus(DG,user,typ='all'):
userData=api.get_user(user)
userID=userData.id
if userID not in DG.nodes():
if typ=='all' or typ=='fr':
print 'adding in user friendships...'
userFriends=api.friends_ids(user)
print user,'as',userID
frNet=nwx.createTwitterFnet(api,user,typ='friends')
DG=nwx.mergeNets(DG,frNet)
if typ=='all' or typ=='fo':
print 'adding in user followerships...'
userFollowers=api.followers_ids(user)
print user,'as',userID
foNet=nwx.createTwitterFnet(api,user,typ='followers')
DG=nwx.mergeNets(DG,foNet)
return DG
def filterProjFile(projname,args):
#As we know the filenames, we can now easily run gdfFilter type analyses
#Use the file route because it provides an audit trail...
print 'In filterProjFile'
typ=args.typ+'_outer'+args.typ2
fn='/'.join([projname,typ+'.gdf'])
print 'Loading file...',fn
DG=nwx.directedNetworkFromGDF(fn)
print DG.order(),DG.size()
addUserFriendships=0
user=''
#use an incluser flag to include fr/fo relations of user(s)?
if args.mindegree!=None or args.indegree!=None or args.outdegree!=None or args.outdegreemax!=None or args.indegreemax!=None:
fpf=filterNet(DG,args.mindegree,args.indegree,args.outdegree,args.outdegreemax,typ,addUserFriendships,user,args.outdegreemax)
return fpf
def filterProjFile2(projname,ftyp='outerfriends'):
typ=ftyp.replace('outer','')
#As we know the filenames, we can now easily run gdfFilter type analyses
#Use the file route because it provides an audit trail...
#typ=args.typ+'_outer'+args.typ2
fn='/'.join([projname,ftyp+'.gdf'])
print 'Loading file...',fn
DG=nwx.directedNetworkFromGDF(fn)
print DG.order(),DG.size()
addUserFriendships=0
user=''
#use an incluser flag to include fr/fo relations of user(s)?
if args.mindegree!=None or args.indegree!=None or args.outdegree!=None or args.outdegreemax!=None or args.indegreemax!=None:
fpf=filterNet(DG,args.mindegree,args.indegree,args.outdegree,args.outdegreemax,typ,addUserFriendships,user,args.outdegreemax)
return fpf
def getUsersFromList(userList):
userList_l =userList.split('/')
user=userList_l[0]
list=userList_l[1]
tmp=newt.listDetailsByScreenName({},api.list_members,user,list)
u=[]
for i in tmp:
u.append(tmp[i].screen_name)
return u
#does py have a switch statement?
if args.filterfile==None:
if args.fname=='scmvESP':
projname=getTimeStampedProjDirName('reports/scmvESP','scmvESP')
else: projname= 'reports/scmvESP/'+args.fname+'/'+nowTime()
checkDir(projname)
f=open(projname+'/settings.txt','wb+')
f.write(repr(args)+'\n')
f.write("To run another filter over this data, use:\n")
f.write("python scmvESP.py -filterfile "+projname+' -typ '+args.typ+'\n')
f.write("with -indegree, -mindegree, -outdegree args as required\n")
f.close()
users=[]
if args.user!=None: users=[args.user]
elif args.users!=None: users=args.users
elif args.fromfile!=None:
fname=args.fromfile
print 'Opening file...',fname
f=open(fname,'r+')
for i in f:
i=i.replace('http://twitter.com/','')
i=i.replace('@','')
print 'Grabbed user',i
users.append(i)
f.close()
elif args.hashtag!=None:
users=getHashtagUsers(args.hashtag,args.tagsample,args.tagfilter,projname)
print users
if args.projection=='default':
args.projection=='false'
elif args.searchterm!=None:
searchterm=' '.join(args.searchterm)
#searchterm=urllib.quote(searchterm)
loc=''
dist=50.0
if args.location!=None:
loc=' '.join(args.location)
if args.dist!=None: dist=args.dist
users=getSearchtermUsers(searchterm,args.tagsample,args.tagfilter,projname,loc,dist)
print users
if args.projection=='default':
args.projection=='false'
elif args.list!=None:
users=getUsersFromList(args.list)
if args.projection=='default':
args.projection=='false'
elif args.lists!=None:
users=[]
for x in args.lists:
users2=getUsersFromList(x)
for u in users2:
if u not in users: users.append(u)
if args.projection=='default':
args.projection=='false'
if users!=[]:
tw=newt.getTwitterUsersDetailsByScreenNames(api,users)
newt.gephiOutputFileByName(api,projname+'/users_innerfriends.gdf', tw)
if args.halt!=None: exit(-1)
if args.filterfile!=None:
projname=args.filterfile
logger(projname,args)
print "Projection status is:",args.projection
if args.projection=='forward':
#The getFriendsProjection doesn't use sample but does max out...
args.sample=''
if args.filterfile==None:
getFriendsView(tw)
if args.mindegree!=None or args.indegree!=None or args.outdegree!=None or args.outdegreemax!=None:
fpf=filterProjFile2(projname)
print "Stopping after forward projection; root call is:"
print "python scmvESP.py -filterfile "+projname +' -projection '+ args.projection
print "Also guessing at [TO DO]:"
print "python scmvGraphCompare.py -compare false -outpath "+projname+" -files "+fpf+" -labels testX"
exit(-1)
elif args.projection=='backward':
#The getFriendsProjection doesn't use sample but does max out...
args.sample=''
getFollowersView(tw)
if args.mindegree!=None or args.indegree!=None or args.outdegree!=None or args.outdegreemax!=None:
filterProjFile2(projname,'outerfollowers')
print "Stopping after backward projection; root call is:"
print "python scmvESP.py -filterfile "+projname +' -projection '+ args.projection
exit(-1)
elif args.projection=='false':
print "As requested, stopping before projection routines"
exit(-1)
if args.filterfile==None:
tw=getSourceList(users,args.typ,args.sample,args.filter)
f=open(projname+'/projectionset.txt','wb+')
for tweep in tw:
f.write(str(tweep)+'\n')
f.close()
if args.typ2!='followers':
args.typ2='friends'
if args.sample2>=0:
getFriendsProjection(tw,args.sample2)
else: getFriendsProjection(tw)
else:
getFollowersProjection(tw)
if args.mindegree!=None or args.indegree!=None or args.outdegree!=None or args.outdegreemax!=None:
fpf=filterProjFile(projname,args)
else:
if args.mindegree!=None or args.indegree!=None or args.outdegree!=None or args.outdegreemax!=None:
projname=args.filterfile
fpf=filterProjFile(projname,args)
print "To run another filter over this data, use:"
print "python scmvESP.py -filterfile "+projname+' -typ '+args.typ
print "with -indegree, -mindegree, -outdegree args as required"
print "Also guessing at [TO DO]:"
print "python scmvGraphCompare.py -compare false -outpath "+projname+" -files "+fpf+" -labels testX"