def normGoogleWall(jresult):
posts = list()
page_count = 0
if type(jresult) == list:
for page in jresult:
if page_count > 10:
# revise the size in the future
break
for post in page["items"]:
published_time = formatGoogleTime(post["published"])
place = formatGooglePlace(post.get("location", ""), 2)
info = post.get("object", "")
if info != "":
text = info.get("content", "")
urls = getGoogleUrls(info.get("attachments", ""))
# a = time.time()
lang = ut.detectLang(text)
# b = time.time()
text_en = ut.translate(text, lang)
# c= time.time()
sentiment = ut.getSentiment(text_en)
# d= time.time()
topic_distri = ut.getTopic(text_en)
tf = ut.wordProcess(text, lang)
# e= time.time()
# print(b-a, c-b, d-c, e-d)
posts.append(getPost(text, text_en, published_time, place, urls, lang, sentiment, topic_distri, tf))
page_count+=1
return posts
def normGoogleWall(jresult):
posts = list()
page_count = 0
if type(jresult) == list:
for page in jresult:
if page_count > 10:
# revise the size in the future
break
for post in page["items"]:
published_time = formatGoogleTime(post["published"])
place = formatGooglePlace(post.get("location", ""), 2)
info = post.get("object", "")
if info != "":
text = info.get("content", "")
urls = getGoogleUrls(info.get("attachments", ""))
# a = time.time()
lang = ut.detectLang(text)
# b = time.time()
text_en = ut.translate(text, lang)
# c= time.time()
sentiment = ut.getSentiment(text_en)
# d= time.time()
topic_distri = ut.getTopic(text_en)
tf = ut.wordProcess(text, lang)
# e= time.time()
# print(b-a, c-b, d-c, e-d)
posts.append(
getPost(text, text_en, published_time, place, urls,
lang, sentiment, topic_distri, tf))
page_count += 1
return posts
def normTwitterWall(wall):
posts = list()
for post in wall:
text = post.get("text", "")
time = formatTwitterTime(post.get("created_at"))
place = formatTwitterPlace(post["geo"], 2)
urls = getTwitterUrls(post)
lang = post.get("lang", "")
if lang == "":
lang = ut.detectLang(text)
# translate text
text_en = ut.translate(text, lang)
sentiment = ut.getSentiment(text_en)
topic_distri = ut.getTopic(text_en)
tf = ut.wordProcess(text, lang)
posts.append(getPost(text, text_en, time, place, urls, lang, sentiment, topic_distri, tf))
return posts
def normTwitterWall(wall):
posts = list()
for post in wall:
text = post.get("text", "")
time = formatTwitterTime(post.get("created_at"))
place = formatTwitterPlace(post["geo"], 2)
urls = getTwitterUrls(post)
lang = post.get("lang", "")
if lang == "":
lang = ut.detectLang(text)
# translate text
text_en = ut.translate(text, lang)
sentiment = ut.getSentiment(text_en)
topic_distri = ut.getTopic(text_en)
tf = ut.wordProcess(text, lang)
posts.append(
getPost(text, text_en, time, place, urls, lang, sentiment,
topic_distri, tf))
return posts
