def acquire_user_by_id(uid):
user_result = user_search.search_by_id(uid, fields=['name', 'profile_image_url'])
user = {}
if user_result:
user['name'] = user_result['name']
user['image'] = user_result['profile_image_url']
return user
def getUsernameByUid(uid):
if not uid:
return None
user = xapian_search_user.search_by_id(int(uid), fields=['name'])
if user:
name = user['name']
return name
return None
def acquire_user_by_id(uid):
user_result = user_search.search_by_id(uid, fields=["name", "profile_image_url"])
user = {}
if user_result:
user["name"] = user_result["name"]
user["image"] = user_result["profile_image_url"]
# print 'user', user
return user
def acquire_user_by_id_v2(uid):
result = user_search.search_by_id(int(uid), fields=['name', 'location', 'followers_count', 'friends_count'])
user = {}
if result:
user['name'] = result['name']
user['location'] = result['location']
user['count1'] = result['followers_count']
user['count2'] = result['friends_count']
return user
def get_u_info(uid_list):
user_info_list = []
row = []
for uid in uid_list:
user = user_search.search_by_id(uid, fields=["_id", "name", "profile_image_url", "friends_count"])
if user:
name = user["name"]
profile_image_user = user["profile_image_url"]
friends_count = user["friends_count"]
else:
name = u"未知"
profile_image_user = u"no"
friends_count = -1
row.append([uid, name, profile_image_user, friends_count])
sort_row = sorted(row, key=lambda x: x[3], reverse=True)
user_info_list = [user[:3] for user in sort_row]
return user_info_list
def read_uid_weibos(topic, date, windowsize, uid):
# change
end_ts = datetime2ts(date)
start_ts = end_ts - Day * windowsize
xapian_search_weibo = getXapianWeiboByTopic(topic, start_ts, end_ts)
query_dict = {"user": uid}
count, results = xapian_search_weibo.search(query=query_dict, fields=weibo_fields_list)
if count == 0:
weibo_list = []
else:
weibo_list = []
for weibo in results():
wid = weibo["_id"]
uid = weibo["user"]
result = user_search.search_by_id(uid, fields=user_fields_list)
if result:
name = result["name"]
location = result["location"]
friends_count = result["friends_count"]
followers_count = result["followers_count"]
created_at = result["created_at"]
statuses_count = result["statuses_count"]
profile_image_url = result["profile_image_url"]
else:
name = u"未知"
location = u"未知"
friends_count = u"未知"
followers_count = u"未知"
created_at = u"未知"
statuses_count = u"未知"
profile_image_url = u"no"
text = weibo["text"]
geo = weibo["geo"]
source = weibo["source"]
timestamp = weibo["timestamp"]
date = ts2date(timestamp)
reposts_count = weibo["reposts_count"]
comments_count = weibo["comments_count"]
weibo_link = weiboinfo2url(uid, wid)
domain = uid2domain(uid)
row = [
wid,
uid,
name,
location,
friends_count,
followers_count,
created_at,
statuses_count,
profile_image_url,
date,
text,
geo,
source,
reposts_count,
comments_count,
weibo_link,
]
weibo_list.append(row)
sort_weibo_list = sorted(weibo_list, key=lambda x: x[9])
return sort_weibo_list
def c_weibo_by_ts(topic, date, windowsize, uid, network_type, cid, rank_method):
real_topic_id = acquire_real_topic_id(topic, date, windowsize)
if not real_topic_id:
return None, None, None
# 该话题存在进行下面的计算
key_pre = str(real_topic_id) + '_' + str(date) + '_' + str(windowsize)
# 选择有向图进行社区信息的计算
if network_type=='source_graph':
key = str(GRAPH_PATH)+key_pre + '_gg_graph.gexf'
elif network_type=='direct_superior_graph':
key = str(GRAPH_PATH)+key_pre + '_ds_udg_graph.gexf'
g = nx.read_gexf(key)
# 获取图结构中节点uid对应的社区包括的节点list
community_user_list = get_community_user(g, uid, cid)
# 考虑节点社区属性存放的位置
# change
end_ts = datetime2ts(date)
start_ts = end_ts - Day * windowsize
xapian_search_weibo = getXapianWeiboByTopic(topic, start_ts, end_ts)
query_dict = {
'$or' : []
}
for uid in community_user_list:
query_dict['$or'].append({'user': int(uid)})
community_info = []
count, weibo_results = xapian_search_weibo.search(query=query_dict, fields= weibo_fields_list)
if count==0:
return None
for weibo in weibo_results():
uid = weibo['user']
_id = weibo['_id']
result = user_search.search_by_id(uid, fields=user_fields_list)
if result:
name = result['name']
location = result['location']
friends_count = result['friends_count']
followers_count = result['followers_count']
created_at = result['created_at']
statuses_count = result['statuses_count']
profile_image_url = result['profile_image_url']
else:
name = u'未知'
location = u'未知'
friends_count = u'未知'
followers_count = u'未知'
created_at = u'未知'
statuses_count = u'未知'
profile_image_url = u'no'
text = weibo['text']
timestamp = weibo['timestamp']
date = ts2date(timestamp)
reposts_count = weibo['reposts_count']
source = weibo['source']
geo = weibo['geo']
comments_count = weibo['comments_count']
sentiment = weibo['sentiment']
sentiment_name = emotions_kv[sentiment]
weibo_link = weiboinfo2url(uid, _id)
community_info.append([_id, name, location, friends_count, followers_count, created_at, statuses_count, profile_image_url, text, date, reposts_count, source, geo, comments_count, sentiment_name,weibo_link, uid, timestamp])
if rank_method == 'reposts_count':
sort_community_info = sorted(community_info, key=lambda x:x[10], reverse=True) #以转发量排序
else:
sort_community_info = sorted(community_info, key=lambda x:x[17]) # 以时间戳排序
return sort_community_info
def get_info(neighbor_list, topic, date, windowsize):
end_ts = datetime2ts(date)
start_ts = end_ts - windowsize * Day
xapian_search_weibo = getXapianWeiboByTopic(topic, start_ts, end_ts)
query_dict = {
'$or' : []
}
for uid in neighbor_list:
query_dict['$or'].append({'user': int(uid)})
neighbor_info = []
count, weibo_results = xapian_search_weibo.search(query=query_dict, fields= weibo_fields_list)
if count==0:
return None, None, None
sentiment_count = {}
for weibo in weibo_results():
uid = weibo['user']
_id = weibo['_id']
result = user_search.search_by_id(uid, fields=user_fields_list)
if result:
name = result['name']
location = result['location']
friends_count = result['friends_count']
followers_count = result['followers_count']
created_at = result['created_at']
statuses_count = result['statuses_count']
profile_image_url = result['profile_image_url']
else:
name = u'未知'
location = u'未知'
friends_count = u'未知'
followers_count = u'未知'
created_at = u'未知'
statuses_count = u'未知'
profile_image_url = u'no'
text = weibo['text']
timestamp = weibo['timestamp']
date = ts2date(timestamp)
reposts_count = weibo['reposts_count']
source = weibo['source']
geo = weibo['geo']
comments_count = weibo['comments_count']
sentiment = weibo['sentiment']
sentiment_name = emotions_kv[sentiment]
weibo_link = weiboinfo2url(uid, _id)
try:
sentiment_count[sentiment] += 1
except KeyError:
sentiment_count[sentiment] = 1
neighbor_info.append([_id, name, location, friends_count, followers_count, created_at, statuses_count, profile_image_url, text, date, reposts_count, source, geo, comments_count, sentiment_name,weibo_link, uid])
sort_neighbor_info = sorted(neighbor_info, key=lambda x:x[10], reverse=True) #以转发量排序
mset = xapian_search_weibo.search(query=query_dict, max_offset=50, mset_direct=True)
top_keyword = top_keywords(gen_mset_iter(xapian_search_weibo, mset, fields=['terms']), top=50)
sort_top_keyword = sorted(top_keyword, key=lambda x:x[1], reverse=True)
new_sentiment_list = []
for sentiment in sentiment_count:
sentiment_ch = emotions_kv[int(sentiment)]
num = sentiment_count[sentiment]
ratio = float(num) / float(count)
new_sentiment_list.append([sentiment_ch, num, ratio])
return sort_neighbor_info, sort_top_keyword, new_sentiment_list, query_dict
def community_result(community_user_list, topic, date, windowsize):
# change
end_ts = datetime2ts(date)
start_ts = end_ts - windowsize * Day
xapian_search_weibo = getXapianWeiboByTopic(topic, start_ts, end_ts)
query_dict = {"$or": []}
for uid in community_user_list:
query_dict["$or"].append({"user": int(uid)})
community_info = []
count, weibo_results = xapian_search_weibo.search(query=query_dict, fields=weibo_fields_list)
if count == 0:
return None, None, None
sentiment_count = {}
for weibo in weibo_results():
uid = weibo["user"]
_id = weibo["_id"]
result = user_search.search_by_id(uid, fields=user_fields_list)
if result:
name = result["name"]
location = result["location"]
friends_count = result["friends_count"]
followers_count = result["followers_count"]
created_at = result["created_at"]
statuses_count = result["statuses_count"]
profile_image_url = result["profile_image_url"]
else:
name = u"未知"
location = u"未知"
friends_count = u"未知"
followers_count = u"未知"
created_at = u"未知"
statuses_count = u"未知"
profile_image_url = u"no"
text = weibo["text"]
timestamp = weibo["timestamp"]
date = ts2date(timestamp)
reposts_count = weibo["reposts_count"]
source = weibo["source"]
geo = weibo["geo"]
comments_count = weibo["comments_count"]
sentiment = weibo["sentiment"]
sentiment_name = emotions_kv[sentiment]
weibo_link = weiboinfo2url(uid, _id)
domain = uid2domain(uid)
try:
sentiment_count[sentiment] += 1
except KeyError:
sentiment_count[sentiment] = 1
community_info.append(
[
_id,
name,
location,
friends_count,
followers_count,
created_at,
statuses_count,
profile_image_url,
text,
date,
reposts_count,
source,
geo,
comments_count,
sentiment_name,
weibo_link,
domain,
]
)
sort_community_info = sorted(community_info, key=lambda x: x[10], reverse=True) # 以转发量排序
mset = xapian_search_weibo.search(query=query_dict, max_offset=50, mset_direct=True)
top_keyword = top_keywords(gen_mset_iter(xapian_search_weibo, mset, fields=["terms"]), top=50)
sort_top_keyword = sorted(top_keyword, key=lambda x: x[1], reverse=True)
new_sentiment_list = []
for sentiment in sentiment_count:
sentiment_ch = emotions_kv[int(sentiment)]
num = sentiment_count[sentiment]
ratio = float(num) / float(count)
new_sentiment_list.append([sentiment_ch, num, ratio])
return sort_community_info, sort_top_keyword, new_sentiment_list, query_dict