about your dataset #11
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Okay, time has passed for a long time, and I forgot how to debug it.I can post some code that I have processed, I hope it will be useful to you
train_id = pickle.load(open("../EANN-KDD18-master/Data/weibo/train_id.pickle", 'rb'))
val_id = pickle.load(open("../EANN-KDD18-master/Data/weibo/validate_id.pickle", 'rb'))
stop_words = process_data_weibo.stopwordslist()
pre_path = 'F:/data/EANN-KDD18-master/Data/weibo/tweets/'
file_list = [pre_path + "test_nonrumor.txt", pre_path + "test_rumor.txt", \
pre_path + "train_nonrumor.txt", pre_path + "train_rumor.txt"]
nonrumor_images = deal_image('F:/data/EANN-KDD18-master/Data/weibo/nonrumor_images/')
rumor_images = deal_image('F:/data/EANN-KDD18-master/Data/weibo/rumor_images/')
#train
for k,f in enumerate(file_list):
f = open(f,encoding='utf-8')
if (k + 1) % 2 == 1:
label = 0 ### real is 0
else:
label = 1 ####fake is 1
lines = f.readlines()
post_id = ""
url = ""
for i, line in enumerate(lines):
if (i+1)%3 ==1 :
post_id = line.split('|')[0]
if (i+1)%3 ==2:
url = (line.lower())
if (i+1)%3 ==0:
line = process_data_weibo.clean_str_sst(line)
seg_list = jieba.cut_for_search(line) #中文分词
new_seg_list = []
for word in seg_list:
if word not in stop_words:
new_seg_list.append(word)
clean_l = ' '.join(new_seg_list)
if len(clean_l) > 10 and post_id in train_id:
describe = []
for x in new_seg_list:
if x not in word2ix:
word2ix[x] = wordcnt
ix2word[wordcnt] = x
wordcnt += 1
describe.append(word2ix[x])
max_seq_len =max(max_seq_len,len(describe))
event = int(train_id[post_id])
max_event = max(max_event,event)
for x in url.split('|'):
image_id = x.split('/')[-1].split(".")[0]
if label==0 and image_id in nonrumor_images:
image_url = 'F:/data/EANN-KDD18-master/Data/weibo/nonrumor_images/' + image_id + '.' + nonrumor_images[image_id]
data.append([describe,image_url,label,event])
elif label==1 and image_id in rumor_images:
image_url = 'F:/data/EANN-KDD18-master/Data/weibo/rumor_images/' + image_id + '.' + rumor_images[image_id]
data.append([describe,image_url,label,event])
elif len(clean_l) > 10 and post_id in val_id:
describe = []
for x in new_seg_list:
if x not in word2ix:
word2ix[x] = wordcnt
ix2word[wordcnt] = x
wordcnt += 1
describe.append(word2ix[x])
max_seq_len =max(max_seq_len,len(describe))
event = int(val_id[post_id])
max_event = max(max_event,event)
for x in url.split('|'):
image_id = x.split('/')[-1].split(".")[0]
if label==0 and image_id in nonrumor_images:
image_url = 'F:/data/EANN-KDD18-master/Data/weibo/nonrumor_images/' + image_id + '.' + nonrumor_images[image_id]
val_data.append([describe,image_url,label,event])
elif label==1 and image_id in rumor_images:
image_url = 'F:/data/EANN-KDD18-master/Data/weibo/rumor_images/' + image_id + '.' + rumor_images[image_id]
val_data.append([describe,image_url,label,event])
…------------------ 原始邮件 ------------------
发件人: ***@***.***>;
发送时间: 2021年5月15日(星期六) 晚上8:30
收件人: ***@***.***>;
抄送: ***@***.***>; ***@***.***>;
主题: Re: [yaqingwang/EANN-KDD18] about your dataset (#11)
Hello, can I ask how you generate validate_id.pickle/train_id.pickle/test_id.pickle?
hello,Do you know how to generate the files now?
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Thank you very much for your reply. Could you tell me the relevant codes of this file of w2v.pickle |
Thank you very much for your reply,Could you tell me the relevant codes of this file of w2v.pickle ?It's very important to me. I'm a beginner. I'm sorry to bother you |
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The code on git is pretty good, you can take a closer look and you can understand the usefulness of each
def get_data(text_only):
#text_only = False
if text_only:
print("Text only")
image_list = []
else:
print("Text and image")
image_list = read_image()
train_data = write_data("train", image_list, text_only)
valiate_data = write_data("validate", image_list, text_only)
test_data = write_data("test", image_list, text_only)
print("loading data...")
# w2v_file = '../Data/GoogleNews-vectors-negative300.bin'
vocab, all_text = load_data(train_data, valiate_data, test_data)
# print(str(len(all_text)))
print("number of sentences: " + str(len(all_text)))
print("vocab size: " + str(len(vocab)))
max_l = len(max(all_text, key=len))
print("max sentence length: " + str(max_l))
word_embedding_path = "../EANN-KDD18-master/Data/weibo/w2v.pickle"
w2v = pickle.load(open(word_embedding_path,"rb"),encoding='bytes')
# print(w2v)
# input("w2v over")
print("word2vec loaded!")
print("num words already in word2vec: " + str(len(w2v)))
add_unknown_words(w2v, vocab)
W, word_idx_map = get_W(w2v)
# # rand_vecs = {}
# # add_unknown_words(rand_vecs, vocab)
W2 = rand_vecs = {}
w_file = open("../EANN-KDD18-master/Data/weibo/word_embedding.pickle", "wb")
pickle.dump([W, W2, word_idx_map, vocab, max_l], w_file)
w_file.close()
return train_data, valiate_data, test_data
…------------------ 原始邮件 ------------------
发件人: ***@***.***>;
发送时间: 2021年5月16日(星期天) 上午10:08
收件人: ***@***.***>;
抄送: ***@***.***>; ***@***.***>;
主题: Re: [yaqingwang/EANN-KDD18] about your dataset (#11)
Hello, can I ask how you generate validate_id.pickle/train_id.pickle/test_id.pickle?
Thank you very much for your reply,Could you tell me the relevant codes of this file of w2v.pickle ?It's very important to me. I'm a beginner. I'm sorry to bother you
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I used Weibo files and it worked ,but I don't know how to use Twitter data.Please tell me whether you useTwitter files for your experiment? |
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Hello, can I ask how you generate validate_id.pickle/train_id.pickle/test_id.pickle?Thank you! |
hello，I have the same problem.could you please tell me how should I do? |
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my email adress is [email protected] |
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I have the same problem. Can you tell me how to solve it? |
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Hello, can I ask how you generate validate_id.pickle/train_id.pickle/test_id.pickle?
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