def analyseArticle(file_name):
# Container of relationships.
relations = {}
# Revisions to compare.
revision_curr = Revision()
revision_prev = Revision()
text_curr = None
# Access the file.
dumpIterator = dump.Iterator(file_name)
# Iterate over the pages.
for page in dumpIterator.readPages():
i = 0
# Iterate over revisions of the article.
for revision in page.readRevisions():
vandalism = False
#print "processing rev", revision.getId()
# Update the information about the previous revision.
revision_prev = revision_curr
if (revision.getSha1() == None):
revision.setSha1(
Text.calculateHash(revision.getText().encode("utf-8")))
if (revision.getSha1() in spam):
vandalism = True
#TODO: SPAM detection: DELETION
if (revision.getComment() != None
and revision.getComment().find(FLAG) > 0):
pass
else:
if (revision_prev.length > PREVIOUS_LENGTH) and (len(
revision.getText()) < CURR_LENGTH) and ((
(len(revision.getText()) - revision_prev.length) /
float(revision_prev.length)) <= CHANGE_PERCENTAGE):
vandalism = True
revision_curr = revision_prev
#if (vandalism):
#print "---------------------------- FLAG 1"
#print "SPAM", revision.getId()
#print revision.getText()
#print
if (not vandalism):
# Information about the current revision.
revision_curr = Revision()
revision_curr.id = i
revision_curr.wikipedia_id = int(revision.getId())
revision_curr.length = len(revision.getText())
revision_curr.timestamp = revision.getTimestamp()
revision_curr.comment = revision.getComment()
# Relation of the current relation.
relation = Relation()
relation.revision = int(revision.getId())
relation.length = len(revision.getText())
# Some revisions don't have contributor.
if (revision.getContributor() != None):
revision_curr.contributor_id = revision.getContributor(
).getId()
revision_curr.contributor_name = revision.getContributor(
).getUsername().encode('utf-8')
relation.author = revision.getContributor().getUsername(
).encode('utf-8')
else:
revision_curr.contributor_id = 'Not Available ' + revision.getId(
)
revision_curr.contribur_name = 'Not Available ' + revision.getId(
)
relation.author = 'Not Available ' + revision.getId()
# Content within the revision.
text_curr = revision.getText().encode('utf-8')
text_curr = text_curr.lower()
revision_curr.content = text_curr
# Perform comparison.
vandalism = determineAuthorship(revision_curr, revision_prev,
text_curr, relation)
if (not vandalism):
#print "NOT SPAM", revision.getId()
# Add the current revision with all the information.
revisions.update(
{revision_curr.wikipedia_id: revision_curr})
relations.update({revision_curr.wikipedia_id: relation})
revision_order.append((revision_curr.wikipedia_id, False))
# Update the fake revision id.
i = i + 1
# Calculate the number of tokens in the revision.
total = 0
for p in revision_curr.ordered_paragraphs:
for paragraph_curr in revision_curr.paragraphs[p]:
for hash_sentence_curr in paragraph_curr.sentences.keys(
):
for sentence_curr in paragraph_curr.sentences[
hash_sentence_curr]:
total = total + len(sentence_curr.words)
revision_curr.total_tokens = total
relation.total_tokens = total
else:
#print "---------------------------- FLAG 2"
#print "SPAM", revision.getId()
#print revision.getText()
#print
revision_order.append((revision_curr.wikipedia_id, True))
revision_curr = revision_prev
spam.append(revision.getSha1())
return (revisions, revision_order, relations)
def analyseArticle(file_name):
# Container of revisions.
revisions = {}
# Revisions to compare.
revision_curr = Revision()
revision_prev = Revision()
text_curr = None
# Access the file.
dumpIterator = dump.Iterator(file_name)
# Iterate over the pages.
for page in dumpIterator.readPages():
i = 0
# Iterate over revisions of the article.
for revision in page.readRevisions():
vandalism = False
# Update the information about the previous revision.
revision_prev = revision_curr
if (revision.getSha1() == None):
revision.setSha1(Text.calculateHash(revision.getText().encode("utf-8")))
if (revision.getSha1() in spam):
vandalism = True
#TODO: SPAM detection: DELETION
if (revision.getComment()!= None and revision.getComment().find(FLAG) > 0):
pass
else:
if (revision_prev.length > PREVIOUS_LENGTH) and (len(revision.getText()) < CURR_LENGTH) and (((len(revision.getText())-revision_prev.length)/float(revision_prev.length)) <= CHANGE_PERCENTAGE):
vandalism = True
revision_curr = revision_prev
#if (vandalism):
#print "---------------------------- FLAG 1"
#print revision.getId()
#print revision.getText()
#print
if (not vandalism):
# Information about the current revision.
revision_curr = Revision()
revision_curr.id = i
revision_curr.wikipedia_id = int(revision.getId())
revision_curr.length = len(revision.getText())
# Some revisions don't have contributor.
if (revision.getContributor() != None):
revision_curr.contributor_id = revision.getContributor().getId()
revision_curr.contributor_name = revision.getContributor().getUsername()
else:
revision_curr.contributor_id = 'Not Available'
revision_curr.contribur_name = 'Not Available'
# Content within the revision.
text_curr = revision.getText().encode('utf-8')
text_curr = text_curr.lower()
revision_curr.content = text_curr
# Perform comparison.
vandalism = determineAuthorship(revision_curr, revision_prev, text_curr)
if (not vandalism):
# Add the current revision with all the information.
revisions.update({revision_curr.wikipedia_id : revision_curr})
# Update the fake revision id.
i = i+1
else:
#print "---------------------------- FLAG 2"
#print revision.getId()
#print revision.getText()
#print
revision_curr = revision_prev
spam.append(revision.getSha1())
return revisions
def getTagDatesFromPage(file_name):
# Compile regexp
reglist = list()
reglist.append({
"tagname":
"maintained",
"regexp":
re.compile(
'\{\{(articleissues\|((?:(?!\}\}).)*\||)|multiple issues\|((?:(?!\}\}).)*\||)|)maintained((\||=)(?:(?!\}\}).)*|)\}\}',
re.IGNORECASE)
})
reglist.append({
"tagname":
"good article",
"regexp":
re.compile(
'\{\{(articleissues\|((?:(?!\}\}).)*\||)|multiple issues\|((?:(?!\}\}).)*\||)|)good article((\||=)(?:(?!\}\}).)*|)\}\}',
re.IGNORECASE)
})
#reglist.append({"tagname": "featured article", "regexp": re.compile('\{\{(articleissues\|((?:(?!\}\}).)*\||)|multiple issues\|((?:(?!\}\}).)*\||)|)featured article((\||=)(?:(?!\}\}).)*|)\}\}', re.IGNORECASE)})
#reglist.append({"tagname": "featured article", "regexp": re.compile('\|currentstatus=FA', re.IGNORECASE)})
reglist.append({
"tagname":
"npov",
"regexp":
re.compile(
'\{\{(articleissues\|((?:(?!\}\}).)*\||)|multiple issues\|((?:(?!\}\}).)*\||)|)(pov|npov)((\||=)(?:(?!\}\}).)*|)\}\}',
re.IGNORECASE)
})
reglist.append({
"tagname":
"disputed",
"regexp":
re.compile(
'\{\{(articleissues\|((?:(?!\}\}).)*\||)|multiple issues\|((?:(?!\}\}).)*\||)|)disputed((\||=)(?:(?!\}\}).)*|)\}\}',
re.IGNORECASE)
})
re_user = re.compile('({{|\[\[)user.*?[:|](.*?)[}/\]|]', re.IGNORECASE)
#"({{|\[\[)user[\s\S]*?[:|]([\s\S]*?)[}/\]|]"
# Access the file.
dumpIterator = dump.Iterator(file_name)
# Revisions to compare.
revision_curr = Revision()
revision_prev = Revision()
text_curr = None
listOfTagChanges = {}
all_contributors = {
"maintained": {},
"good article": {},
"featured article": {},
"npov": {},
"disputed": {}
}
# Iterate over the pages.
for page in dumpIterator.readPages():
# Iterate over revisions of the article.
i = 0
prev_matched = list()
for revision in page.readRevisions():
revision.wikipedia_id = int(revision.getId())
revision.timestamp = revision.getTimestamp()
# Some revisions don't have contributor.
if (revision.getContributor() != None):
revision.contributor_id = revision.getContributor().getId()
revision.contributor_name = revision.getContributor(
).getUsername()
else:
revision.contributor_id = 'Not Available'
revision.contribur_name = 'Not Available'
text_curr = revision.getText()
if (text_curr):
text_curr = text_curr.encode('utf-8')
text_curr = text_curr.lower()
else:
continue
matched = list()
aux = list()
for regexp in reglist:
m = regexp["regexp"].search(text_curr)
if m:
mc = re_user.split(m.group(0))
i = 2
users = []
users.append(mc[2])
while (i + 3 < len(mc)):
#print m[i+3]
users.append(mc[i + 3])
i = i + 3
#print regexp["tagname"], contributor
#print regexp["tagname"], users
matched.append(regexp["tagname"])
aux.append((regexp["tagname"], users))
##
#m_user = re_user.search(m.group(0))
#contributor = m_user.group(2)
if "|currentstatus=FA" in text_curr:
matched.append("featured article")
aux.append((revision.contributor_name, "featured article"))
# Calculate additions
for (match, contributor) in aux:
if not (match in prev_matched):
if not (revision.timestamp in listOfTagChanges.keys()):
listOfTagChanges[revision.timestamp] = list()
listOfTagChanges[revision.timestamp].append({
"rev":
revision.wikipedia_id,
"type":
"addition",
"tagname":
match,
"wikiname":
revision.contributor_name,
"timestamp":
revision.timestamp,
"date":
datetime.datetime.fromtimestamp(int(
revision.timestamp)).strftime('%Y-%m-%d %H:%M:%S')
})
all_contributors[match].update({
revision.timestamp: {
"rev":
revision.wikipedia_id,
"user":
contributor,
"date":
datetime.datetime.fromtimestamp(int(
revision.timestamp)).strftime('%Y-%m-%d %H:%M:%S')
}
})
# Calculate removals
for match in prev_matched:
if not (match in matched):
if not (revision.timestamp in listOfTagChanges.keys()):
listOfTagChanges[revision.timestamp] = list()
listOfTagChanges[revision.timestamp].append({
"rev":
revision.wikipedia_id,
"type":
"removal",
"tagname":
match,
"wikiname":
revision.contributor_name,
"timestamp":
revision.timestamp,
"date":
datetime.datetime.fromtimestamp(int(
revision.timestamp)).strftime('%Y-%m-%d %H:%M:%S')
})
prev_matched = matched
return listOfTagChanges, all_contributors
def analyseArticle(file_name):
# Container of relationships.
relations = {}
# Revisions to compare.
revision_curr = Revision()
revision_prev = Revision()
text_curr = None
# Access the file.
dumpIterator = dump.Iterator(file_name)
# Iterate over the pages.
for page in dumpIterator.readPages():
i = 0
# Iterate over revisions of the article.
for revision in page.readRevisions():
vandalism = False
#print "processing rev", revision.getId()
# Update the information about the previous revision.
revision_prev = revision_curr
if (revision.getSha1() == None):
revision.setSha1(Text.calculateHash(revision.getText().encode("utf-8")))
if (revision.getSha1() in spam):
vandalism = True
#TODO: SPAM detection: DELETION
if (revision.getComment()!= None and revision.getComment().find(FLAG) > 0):
pass
else:
if (revision_prev.length > PREVIOUS_LENGTH) and (len(revision.getText()) < CURR_LENGTH) and (((len(revision.getText())-revision_prev.length)/float(revision_prev.length)) <= CHANGE_PERCENTAGE):
vandalism = True
revision_curr = revision_prev
#if (vandalism):
#print "---------------------------- FLAG 1"
#print "SPAM", revision.getId()
#print revision.getText()
#print
if (not vandalism):
# Information about the current revision.
revision_curr = Revision()
revision_curr.id = i
revision_curr.wikipedia_id = int(revision.getId())
revision_curr.length = len(revision.getText())
revision_curr.timestamp = revision.getTimestamp()
revision_curr.comment = revision.getComment()
# Relation of the current relation.
relation = Relation()
relation.revision = int(revision.getId())
relation.length = len(revision.getText())
# Some revisions don't have contributor.
if (revision.getContributor() != None):
revision_curr.contributor_id = revision.getContributor().getId()
revision_curr.contributor_name = revision.getContributor().getUsername().encode('utf-8')
relation.author = revision.getContributor().getUsername().encode('utf-8')
else:
revision_curr.contributor_id = 'Not Available ' + revision.getId()
revision_curr.contribur_name = 'Not Available ' + revision.getId()
relation.author = 'Not Available ' + revision.getId()
# Content within the revision.
text_curr = revision.getText().encode('utf-8')
text_curr = text_curr.lower()
revision_curr.content = text_curr
# Perform comparison.
vandalism = determineAuthorship(revision_curr, revision_prev, text_curr, relation)
if (not vandalism):
#print "NOT SPAM", revision.getId()
# Add the current revision with all the information.
revisions.update({revision_curr.wikipedia_id : revision_curr})
relations.update({revision_curr.wikipedia_id : relation})
revision_order.append((revision_curr.wikipedia_id, False))
# Update the fake revision id.
i = i+1
# Calculate the number of tokens in the revision.
total = 0
for p in revision_curr.ordered_paragraphs:
for paragraph_curr in revision_curr.paragraphs[p]:
for hash_sentence_curr in paragraph_curr.sentences.keys():
for sentence_curr in paragraph_curr.sentences[hash_sentence_curr]:
total = total + len(sentence_curr.words)
revision_curr.total_tokens = total
relation.total_tokens = total
else:
#print "---------------------------- FLAG 2"
#print "SPAM", revision.getId()
#print revision.getText()
#print
revision_order.append((revision_curr.wikipedia_id, True))
revision_curr = revision_prev
spam.append(revision.getSha1())
return (revisions, revision_order, relations)
def analyseArticle(file_name):
# Container of revisions.
revisions = {}
revision_order = []
# Revisions to compare.
revision_curr = Revision()
revision_prev = Revision()
text_curr = None
# Access the file.
dumpIterator = dump.Iterator(file_name)
# Iterate over the pages.
for page in dumpIterator.readPages():
i = 0
# Iterate over revisions of the article.
for revision in page.readRevisions():
vandalism = False
# Update the information about the previous revision.
revision_prev = revision_curr
if (revision.getSha1() == None):
revision.setSha1(
Text.calculateHash(revision.getText().encode("utf-8")))
if (revision.getSha1() in spam):
vandalism = True
#TODO: SPAM detection: DELETION
if (revision.getComment() != None
and revision.getComment().find(FLAG) > 0):
pass
else:
if (revision_prev.length > PREVIOUS_LENGTH) and (len(
revision.getText()) < CURR_LENGTH) and ((
(len(revision.getText()) - revision_prev.length) /
float(revision_prev.length)) <= CHANGE_PERCENTAGE):
print "VANDALISM: CHANGE PERCETANGE"
vandalism = True
#if (vandalism):
#print "---------------------------- FLAG 1"
#print revision.getId()
#print revision.getText()
#print
if (not vandalism):
# Information about the current revision.
revision_curr = Revision()
revision_curr.id = i
revision_curr.wikipedia_id = int(revision.getId())
revision_curr.length = len(revision.getText())
# Some revisions don't have contributor.
if (revision.getContributor() != None):
revision_curr.contributor_id = revision.getContributor(
).getId()
revision_curr.contributor_name = revision.getContributor(
).getUsername()
else:
revision_curr.contributor_id = 'Not Available'
revision_curr.contribur_name = 'Not Available'
# Content within the revision.
text_curr = revision.getText().encode('utf-8')
text_curr = text_curr.lower()
revision_curr.content = text_curr
# Perform comparison.
vandalism = determineAuthorship(revision_curr, revision_prev,
text_curr)
if (not vandalism):
# Add the current revision with all the information.
revisions.update(
{revision_curr.wikipedia_id: revision_curr})
# Update the fake revision id.
i = i + 1
# Update the index of processed revisions.
revision_order.append((revision_curr.wikipedia_id, False))
else:
#print "detected vandalism in here ...................................."
#print "---------------------------- FLAG 2"
#print revision.getId()
#print revision.getText()
#print
spam.append(revision.getSha1())
revision_order.append((revision_curr.wikipedia_id, True))
revision_curr = revision_prev
else:
# revision.getText()
# #print
spam.append(revision.getSha1())
revision_order.append((revision_curr.wikipedia_id, True))
revision_curr = revision_prev
return (revisions, revision_order)
def analyseArticle(file_name):
# Container of relationships.
relations = {}
# Revisions to compare.
revision_curr = Revision()
revision_prev = Revision()
text_curr = None
# Access the file.
dumpIterator = mwIterator.from_file(open_file(file_name))
# Iterate over the pages.
for page in dumpIterator:
i = 0
# Iterate over revisions of the article.
for revision in page:
vandalism = False
# Update the information about the previous revision.
revision_prev = revision_curr
if (revision.sha1 == None):
revision.sha1 = Text.calculateHash(revision.text)
if (revision.sha1 in spam):
vandalism = True
#TODO: SPAM detection: DELETION
if (revision.comment!= None and revision.comment.find(FLAG) > 0):
pass
else:
if (revision_prev.length > PREVIOUS_LENGTH) and (len(revision.text) < CURR_LENGTH) and (((len(revision.text)-revision_prev.length)/float(revision_prev.length)) <= CHANGE_PERCENTAGE):
vandalism = True
revision_curr = revision_prev
if (not vandalism):
# Information about the current revision.
revision_curr = Revision()
revision_curr.id = i
revision_curr.wikipedia_id = int(revision.id)
revision_curr.length = len(revision.text)
revision_curr.timestamp = revision.timestamp
# Relation of the current relation.
relation = Relation()
relation.revision = int(revision.id)
relation.length = len(revision.text)
# Some revisions don't have contributor.
if (revision.contributor != None):
revision_curr.contributor_id = revision.contributor.id
revision_curr.contributor_name = revision.contributor.user_text
relation.author = revision.contributor.user_text
else:
revision_curr.contributor_id = 'Not Available ' + revision.id
revision_curr.contribur_name = 'Not Available ' + revision.id
relation.author = 'Not Available ' + revision.id
# Content within the revision.
text_curr = revision.text.lower()
# Perform comparison.
vandalism = determineAuthorship(revision_curr, revision_prev, text_curr, relation)
if (not vandalism):
# Add the current revision with all the information.
revisions.update({revision_curr.wikipedia_id : revision_curr})
relations.update({revision_curr.wikipedia_id : relation})
revision_order.append((revision_curr.wikipedia_id, False))
# Update the fake revision id.
i = i+1
# Calculate the number of tokens in the revision.
total = 0
for p in revision_curr.ordered_paragraphs:
for paragraph_curr in revision_curr.paragraphs[p]:
for hash_sentence_curr in paragraph_curr.sentences.keys():
for sentence_curr in paragraph_curr.sentences[hash_sentence_curr]:
total = total + len(sentence_curr.words)
revision_curr.total_tokens = total
relation.total_tokens = total
else:
revision_order.append((revision_curr.wikipedia_id, True))
revision_curr = revision_prev
spam.append(revision.sha1)
return (revisions, revision_order, relations)
def analyseArticle(file_name):
# Container of relationships.
relations = {}
# Revisions to compare.
revision_curr = Revision()
revision_prev = Revision()
text_curr = None
# Access the file.
dumpIterator = mwIterator.from_file(open_file(file_name))
# Iterate over the pages.
for page in dumpIterator:
i = 0
# Iterate over revisions of the article.
for revision in page:
vandalism = False
# Update the information about the previous revision.
revision_prev = revision_curr
if (revision.sha1 == None):
revision.sha1 = Text.calculateHash(revision.text)
if (revision.sha1 in spam):
vandalism = True
#TODO: SPAM detection: DELETION
if (revision.comment!= None and revision.comment.find(FLAG) > 0):
pass
else:
if (revision_prev.length > PREVIOUS_LENGTH) and (len(revision.text) < CURR_LENGTH) and (((len(revision.text)-revision_prev.length)/float(revision_prev.length)) <= CHANGE_PERCENTAGE):
vandalism = True
revision_curr = revision_prev
if (not vandalism):
# Information about the current revision.
revision_curr = Revision()
revision_curr.id = i
revision_curr.wikipedia_id = int(revision.id)
revision_curr.length = len(revision.text)
revision_curr.timestamp = revision.timestamp
# Relation of the current relation.
relation = Relation()
relation.revision = int(revision.id)
relation.length = len(revision.text)
# Some revisions don't have contributor.
if (revision.contributor != None):
revision_curr.contributor_id = revision.contributor.id
revision_curr.contributor_name = revision.contributor.user_text
relation.author = revision.contributor.user_text
else:
revision_curr.contributor_id = 'Not Available ' + revision.id
revision_curr.contribur_name = 'Not Available ' + revision.id
relation.author = 'Not Available ' + revision.id
# Content within the revision.
text_curr = revision.text.lower()
# Perform comparison.
vandalism = determineAuthorship(revision_curr, revision_prev, text_curr, relation)
if (not vandalism):
# Add the current revision with all the information.
revisions.update({revision_curr.wikipedia_id : revision_curr})
relations.update({revision_curr.wikipedia_id : relation})
revision_order.append((revision_curr.wikipedia_id, False))
# Update the fake revision id.
i = i+1
# Calculate the number of tokens in the revision.
total = 0
for p in revision_curr.ordered_paragraphs:
for paragraph_curr in revision_curr.paragraphs[p]:
for hash_sentence_curr in paragraph_curr.sentences.keys():
for sentence_curr in paragraph_curr.sentences[hash_sentence_curr]:
total = total + len(sentence_curr.words)
revision_curr.total_tokens = total
relation.total_tokens = total
else:
revision_order.append((revision_curr.wikipedia_id, True))
revision_curr = revision_prev
spam.append(revision.sha1)
return (revisions, revision_order, relations)
