chengjun

import urllib2
from bs4 import BeautifulSoup
import sys

# get the link for each chapter
url = "http://www.23wx.com/html/50/50550/" # 三界独尊
content = urllib2.urlopen(url).read() 
soup = BeautifulSoup(content) 
links = soup.find_all('td')[1000:]

chengjun

# -*- coding: utf-8 -*-
"""
Created on Tue Jul 07 15:40:57 2015

@author: chengwang6
"""
import urllib2
from bs4 import BeautifulSoup
## Set the seed of crawler
seed = 'https://scholar.google.nl/citations?user=nNdt_G8AAAAJ&hl=en&oe=ASCII'

chengjun

with open("F:/百度云同步盘/Computational Communication/Data/占中数据20150328/zz-hk-2013.1-2013.3.rtf") as f:
   news = f.readlines()
    

def stringclean(s):
    s = s.replace(r'\loch\af0\hich\af0\dbch\f15 \b\cf6 ', '')
    s = s.replace(r'\loch\af0\hich\af0\dbch\f15 \b0\cf0 ', '')
    s = s.replace('\par', '').replace('\n', '')
    return s

chengjun

### Title: Back to basics: High quality plots using base R graphics
###	An interactive tutorial for the Davis R Users Group meeting on April 24, 2015
###
### Date created: 20150418
### Last updated: 20150423
###
### Author: Michael Koontz
### Email: [email protected]
###	Twitter: @michaeljkoontz
###

chengjun

require(igraph)
# generate a social graph
node_number = 100
g = barabasi.game(node_number) ; plot(g)

seeds_num = 1
set.seed(2014); diffusers = sample(V(g),seeds_num) ; diffusers
infected =list()
infected[[1]]= diffusers

chengjun

# -*- coding: utf-8 -*-
"""
Created on Wed Aug 13 21:28:10 2014

@author: v_chjwang
"""

from os import listdir
import glob 
from collections import defaultdict

chengjun

#!/usr/bin/env python
# -*- coding: utf8 -*-

from weibo import APIClient
import urllib2
import urllib
import sys
import time
from time import clock
import random

chengjun

import sys
from collections import defaultdict, Counter
import glob


reload(sys)
sys.setdefaultencoding('utf8')


path = "D:/chengjun/renren/"

chengjun

‘’‘
step3: delte duplicates, sort data and save data
’‘’

import os
import glob
from collections import defaultdict

path = "D:/renren/friends_sorted/"

chengjun

'''
# Step2: split the duplicated data into about 2000+ files by user ids
# to prepare for deleting the duplicated ties
''' 

from collections import defaultdict

path = "D:/renren/"

bigfile = open(path + "friends_all.txt")