(via these docs) | 10-06-19
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import subjectivity
from nltk.sentiment import SentimentAnalyzer
from nltk.sentiment.util import *
subjective and objective sentences from the nltk for practice¶n_instances = 100
subj_docs = [(sent, 'subj') for sent in subjectivity.sents(categories='subj')[:n_instances]]
obj_docs = [(sent, 'obj') for sent in subjectivity.sents(categories='obj')[:n_instances]]
test and train for both subj and obj¶train_subj_docs = subj_docs[:80]
test_subj_docs = subj_docs[80:100]
train_obj_docs = obj_docs[:80]
test_obj_docs = obj_docs[80:100]
test and train sets¶training_docs = train_subj_docs + train_obj_docs
testing_docs = test_subj_docs + test_obj_docs
# training_docs
SentimentAnalyzer to mark negation in training docs¶sentim_analyzer = SentimentAnalyzer()
# WTF IS MARK_NEGATION
all_words_neg = sentim_analyzer.all_words([mark_negation(doc) for doc in training_docs])
training_docs
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'follow',
'one',
"woman's",
'hypnotic',
'journey',
'to',
'discover',
'her',
'true',
'self',
'.',
'.',
'.'],
'obj'),
(['decent-but-dull',
'dek',
'loves',
'shirley',
',',
'so',
'much',
'so',
'that',
'he',
'humiliates',
'her',
'by',
'proposing',
'without',
'warning',
'on',
'national',
'television',
'.'],
'obj'),
(['since',
'all',
'her',
'architects',
'are',
'either',
'busy',
'otherwise',
'or',
'too',
'conservative',
'in',
'style',
',',
'this',
'ambivalent',
'honour',
'falls',
'to',
'numerobis',
'.'],
'obj'),
(["there's",
'a',
'story',
'that',
'goes',
'around',
'the',
'town',
'of',
'darkness',
'falls',
'about',
'her',
',',
'and',
"she's",
'called',
'the',
'tooth',
'fairy',
'.'],
'obj'),
(['a',
'strange',
'film',
'employing',
'old',
'home',
'movies',
'and',
'newly',
'shot',
'footage',
'in',
'an',
'effort',
'to',
'expose',
'one',
'hungarian',
'family',
'and',
'their',
'mutiple',
'problems',
'from',
'the',
'1940s',
'to',
'current',
'.'],
'obj'),
(['matsumoto',
'and',
'sawako',
'were',
'a',
'happy',
'couple',
',',
'but',
'meddling',
'parents',
'and',
'chase',
'for',
'success',
'push',
'the',
'boy',
'to',
'a',
'tragic',
'choice',
'.'],
'obj'),
(['elvis',
'teams',
'up',
'with',
'jack',
'(',
'ossie',
'davis',
')',
',',
'a',
'fellow',
'nursing',
'home',
'resident',
'who',
'thinks',
'that',
'he',
'is',
'actually',
'president',
'john',
'f',
'.',
'kennedy',
',',
'and',
'the',
'two',
'valiant',
'old',
'codgers',
'sally',
'forth',
'to',
'battle',
'an',
'evil',
'egyptian',
'entity',
'who',
'has',
'chosen',
'their',
'long-term',
'care',
'facility',
'as',
'his',
'happy',
'hunting',
'grounds',
'.'],
'obj'),
(['everywhere',
'he',
'goes',
'he',
'is',
'plagued',
'by',
'cats',
'and',
'when',
'by',
'chance',
'he',
'meets',
'carol',
'on',
'a',
'lonely',
'highway',
'they',
'must',
'begin',
'a',
'journey',
',',
'avoiding',
'the',
'mysterious',
'private',
'detective',
'mr',
'barlow',
'and',
'the',
'terrifying',
'inhuman',
'creature',
'jack',
',',
'to',
'uncover',
'the',
'dark',
'truth',
'to',
"charlie's",
'life',
'.'],
'obj'),
(['used',
'to',
'living',
'in',
'poverty',
',',
'it',
'seemed',
'impossible',
'for',
'cass',
'and',
'cary',
'to',
'have',
'a',
'comfortable',
'and',
'bountiful',
'life',
'until',
'doqa',
'gracia',
'comes',
'to',
'bring',
'them',
'into',
'her',
'home',
'.'],
'obj'),
(['the',
'story',
'of',
'a',
'normal',
'family',
'in',
'which',
'come',
'out',
'the',
'dreams',
'of',
'those',
'who',
'have',
'lost',
'their',
'possibilities',
'and',
'of',
'those',
'who',
'want',
'to',
'realize',
'them',
'.'],
'obj'),
(['with',
'grit',
'and',
'determination',
'molly',
'guides',
'the',
'girls',
'on',
'an',
'epic',
'journey',
',',
'one',
'step',
'ahead',
'of',
'the',
'authorities',
',',
'over',
'1',
',',
'500',
'miles',
'of',
"australia's",
'outback',
'in',
'search',
'of',
'the',
'rabbit-proof',
'fence',
'that',
'bisects',
'the',
'continent',
'and',
'will',
'lead',
'them',
'home',
'.'],
'obj'),
(['they',
'nevertherless',
'feel',
'responsible',
'to',
'protect',
'the',
'flag',
'until',
"monday's",
'ceremony',
'.'],
'obj'),
(['the',
'doctor',
'realizes',
"it''s",
'a',
'love',
'virus',
'so',
'he',
'advises',
'him',
'to',
'woo',
'the',
'girl',
'somehow',
',',
'not',
'realizing',
'that',
'munnabhai',
'has',
'fallen',
'for',
'none',
'other',
'than',
'his',
'own',
'younger',
'sister',
'komal',
'.'],
'obj'),
(['however',
',',
'he',
'can',
'only',
'inhabit',
'the',
'body',
'of',
'a',
'child',
'for',
'a',
'short',
'time',
'.'],
'obj'),
(['years',
'later',
',',
'on',
'a',
'hunting',
'trip',
'in',
'the',
'maine',
'woods',
',',
'they',
'are',
'overtaken',
'by',
'a',
'blizzard',
',',
'a',
'vicious',
'storm',
'in',
'which',
'something',
'much',
'more',
'ominous',
'moves',
'.'],
'obj'),
(['consequently',
',',
'what',
'begins',
'as',
'an',
'enthusiastic',
'road',
'trip',
'is',
'soon',
'plagued',
'with',
'mysterious',
'roadside',
'obstacles',
'that',
'threaten',
'to',
'prevent',
'the',
'boys',
'from',
'ever',
'making',
'it',
'to',
'the',
'competition',
'.'],
'obj'),
(['when',
'she',
'gets',
'into',
'trouble',
'with',
'the',
'police',
'simon',
'represses',
'his',
'death',
'wish',
'and',
'decides',
'to',
'help',
'her',
'out',
'.'],
'obj'),
(['chon',
'then',
'travels',
'to',
'new',
'york',
'for',
'roy',
"o'bannon",
'(',
'owen',
'wilson',
')',
'.'],
'obj'),
(['not',
'only',
'must',
'they',
'overcome',
'an',
'enemy',
'adept',
'at',
'technological',
'witchery',
',',
'they',
'must',
'overcome',
'the',
'curse',
'that',
'marks',
'their',
'destiny',
'.'],
'obj'),
(['their',
'life',
'becomes',
'less',
'ordinary',
'when',
'they',
'encounter',
'herb',
',',
'a',
'mischievous',
'and',
'malevolent',
'geek',
'.'],
'obj'),
(['they', 'call', 'themselves', 'd', '.', 'e', '.', 'b', '.', 's', '.'],
'obj'),
(['the',
'story',
'starts',
'with',
'hakimi',
',',
'a',
'freelance',
'scriptwriter',
'who',
'is',
'on',
'his',
'way',
'to',
'send',
'his',
'7-year-old',
'daughter',
',',
'imelda',
',',
'to',
'his',
"ex-wife's",
'house',
'on',
'one',
'stormy',
'night',
'.'],
'obj'),
(['they',
'follow',
'leads',
',',
'informants',
'turn',
'up',
'dead',
',',
"nick's",
'wife',
'is',
'unhappy',
"he's",
'back',
'on',
'the',
'street',
',',
"henry's",
'protective',
'of',
'the',
'dead',
"cop's",
'wife',
'.'],
'obj'),
(['the',
'second',
'part',
'of',
'aki',
'kaurismä',
';',
"ki's",
'"',
'finland',
'"',
'trilogy',
',',
'the',
'film',
'follows',
'a',
'man',
'who',
'arrives',
'in',
'helsinki',
'and',
'gets',
'beaten',
'up',
'so',
'severely',
'he',
'develops',
'amnesia',
'.'],
'obj'),
(['soon',
'after',
'the',
'accident',
',',
'the',
'survivors',
'of',
'the',
'accident',
'start',
'dropping',
'like',
'flies',
'.'],
'obj'),
(['edgar',
'becomes',
'intent',
'on',
'laying',
'down',
'some',
'new',
'rules',
'and',
'turning',
'his',
'coddled',
'son',
'into',
'someone',
'who',
'can',
'take',
'on',
'the',
'family',
'farm',
'.'],
'obj'),
(['bound',
'by',
'a',
'long',
'red',
'cord',
',',
'a',
'young',
'couple',
'wanders',
'in',
'search',
'of',
'something',
'they',
'have',
'forgotten',
'.'],
'obj'),
(['sudden',
'fame',
'does',
'not',
'seem',
'to',
'solve',
'everything',
',',
'however',
'.'],
'obj'),
(['with',
'no',
'option',
',',
'joe',
'and',
'katsuragi',
'must',
'use',
'their',
'martial',
'arts',
'skills',
'to',
'fight',
'in',
'the',
'muscle',
'dome',
'.'],
'obj'),
(['drawing',
'from',
'his',
'time',
'with',
'the',
'kids',
',',
'he',
'writes',
'a',
'story',
'about',
'children',
'who',
"don't",
'want',
'to',
'grow',
'up',
'.'],
'obj'),
(["she's",
'an',
'artist',
',',
'but',
"hasn't",
'picked',
'up',
'a',
'brush',
'in',
'a',
'year',
'.'],
'obj'),
(['when',
'his',
'daughter',
'is',
'kidnapped',
'and',
'held',
'in',
'exchange',
'for',
'priceless',
'diamonds',
',',
'the',
'leader',
'of',
'a',
'crew',
'of',
'highly',
'skilled',
'urban',
'thieves',
'(',
'dmx',
')',
'forges',
'an',
'unlikely',
'alliance',
'with',
'a',
'taiwanese',
'intelligence',
'officer',
'(',
'jet',
'li',
')',
'to',
'rescue',
'her',
'.'],
'obj'),
(['"',
'garmento',
'"',
'tells',
'the',
'other',
'side',
'of',
'the',
'story',
',',
'with',
'a',
'dark',
'and',
'satirical',
'look',
'at',
'new',
"york's",
'wholesale',
'garment',
'industry',
',',
'where',
'shady',
'deals',
'are',
'made',
'for',
'a',
'buck',
'and',
'ruthlessness',
'is',
'a',
'prerequisite',
'for',
'career',
'success',
'.'],
'obj'),
(['rudy',
'yellowshirt',
'is',
'an',
'investigator',
'with',
'the',
'police',
'department',
'and',
'witnesses',
'firsthand',
'the',
'painful',
'legacy',
'of',
'indian',
'existence',
'.'],
'obj'),
(['journeying',
'from',
'the',
'vietnam',
'war',
'to',
'pulaski',
',',
'tennessee',
'and',
'back',
'to',
'vietnam',
',',
'daughter',
'from',
'danang',
'tensely',
'unfolds',
'as',
'cultural',
'differences',
'and',
'the',
'years',
'of',
'separation',
'take',
'their',
'toll',
'in',
'a',
'riveting',
'film',
'about',
'longing',
'and',
'the',
'personal',
'legacy',
'of',
'war',
'.'],
'obj'),
(['each',
'weekend',
'they',
'come',
'back',
'with',
'nothing',
'but',
'a',
'hangover',
'.'],
'obj')]
all_words_neg[25:45]
['.', 'and', 'just', 'enough', 'science', 'to', 'send', 'you', 'home', 'thinking', '.', 'it', 'is', 'not', 'a_NEG', 'mass-market_NEG', 'entertainment_NEG', 'but_NEG', 'an_NEG', 'uncompromising_NEG']
This is one of many ways we can determine sentiment
unigram_word_feats to get unigrams features¶unigram_feats = sentim_analyzer.unigram_word_feats(all_words_neg, min_freq=4)
len(unigram_feats)
83
sentim_analyzer.add_feat_extractor(extract_unigram_feats, unigrams=unigram_feats)
training_set = sentim_analyzer.apply_features(training_docs)
training_set[:1]
[({'contains(.)': True, 'contains(the)': False, 'contains(,)': True, 'contains(a)': True, 'contains(and)': True, 'contains(of)': False, 'contains(to)': False, 'contains(is)': True, 'contains(in)': False, 'contains(with)': False, 'contains(it)': False, 'contains(that)': False, 'contains(his)': False, 'contains(on)': False, 'contains(for)': False, 'contains(an)': False, 'contains(who)': False, 'contains(by)': False, 'contains(he)': False, 'contains(from)': False, 'contains(her)': False, 'contains(")': False, 'contains(film)': False, 'contains(as)': False, 'contains(this)': False, 'contains(movie)': False, 'contains(their)': False, 'contains(but)': False, 'contains(one)': True, 'contains(at)': False, 'contains(about)': True, 'contains(the_NEG)': False, 'contains(a_NEG)': False, 'contains(to_NEG)': False, 'contains(are)': False, "contains(there's)": False, 'contains(()': False, 'contains(story)': False, 'contains(when)': False, 'contains(so)': False, 'contains(be)': False, 'contains(,_NEG)': False, 'contains())': False, 'contains(they)': False, 'contains(you)': False, 'contains(not)': False, 'contains(have)': False, 'contains(like)': False, 'contains(will)': False, 'contains(all)': False, 'contains(into)': False, 'contains(out)': False, 'contains(she)': False, 'contains(what)': False, 'contains(life)': False, 'contains(has)': False, 'contains(its)': False, 'contains(only)': False, 'contains(more)': False, 'contains(even)': False, 'contains(--)': False, 'contains(:)': False, 'contains(can)': False, 'contains(;)': False, 'contains(home)': False, 'contains(look)': False, "contains(it's)": False, 'contains(if)': False, 'contains(where)': False, 'contains(most)': False, 'contains(him)': False, 'contains(search)': False, 'contains(but_NEG)': False, 'contains(love)': False, 'contains(both)': False, 'contains(make)': False, 'contains(begins)': False, 'contains(some)': False, 'contains(two)': False, 'contains(of_NEG)': False, 'contains(made)': False, 'contains(which)': False, 'contains(them)': False}, 'subj')]
test_set = sentim_analyzer.apply_features(testing_docs)
test_set[:1]
[({'contains(.)': True, 'contains(the)': True, 'contains(,)': False, 'contains(a)': True, 'contains(and)': False, 'contains(of)': True, 'contains(to)': False, 'contains(is)': False, 'contains(in)': False, 'contains(with)': True, 'contains(it)': False, 'contains(that)': False, 'contains(his)': False, 'contains(on)': False, 'contains(for)': True, 'contains(an)': False, 'contains(who)': False, 'contains(by)': False, 'contains(he)': False, 'contains(from)': False, 'contains(her)': False, 'contains(")': False, 'contains(film)': False, 'contains(as)': False, 'contains(this)': False, 'contains(movie)': False, 'contains(their)': False, 'contains(but)': False, 'contains(one)': False, 'contains(at)': False, 'contains(about)': False, 'contains(the_NEG)': False, 'contains(a_NEG)': False, 'contains(to_NEG)': False, 'contains(are)': False, "contains(there's)": False, 'contains(()': False, 'contains(story)': False, 'contains(when)': False, 'contains(so)': False, 'contains(be)': False, 'contains(,_NEG)': False, 'contains())': False, 'contains(they)': False, 'contains(you)': False, 'contains(not)': False, 'contains(have)': False, 'contains(like)': False, 'contains(will)': False, 'contains(all)': False, 'contains(into)': False, 'contains(out)': False, 'contains(she)': False, 'contains(what)': False, 'contains(life)': False, 'contains(has)': False, 'contains(its)': False, 'contains(only)': False, 'contains(more)': False, 'contains(even)': False, 'contains(--)': False, 'contains(:)': False, 'contains(can)': False, 'contains(;)': False, 'contains(home)': False, 'contains(look)': False, "contains(it's)": False, 'contains(if)': False, 'contains(where)': False, 'contains(most)': False, 'contains(him)': False, 'contains(search)': False, 'contains(but_NEG)': False, 'contains(love)': False, 'contains(both)': False, 'contains(make)': False, 'contains(begins)': False, 'contains(some)': False, 'contains(two)': False, 'contains(of_NEG)': False, 'contains(made)': False, 'contains(which)': False, 'contains(them)': False}, 'subj')]
trainer = NaiveBayesClassifier.train
classifier = sentim_analyzer.train(trainer, training_set)
Training classifier
for key,value in sorted(sentim_analyzer.evaluate(test_set).items()):
print('{0}: {1}'.format(key,value))
Evaluating NaiveBayesClassifier results... Accuracy: 0.8 F-measure [obj]: 0.8 F-measure [subj]: 0.8 Precision [obj]: 0.8 Precision [subj]: 0.8 Recall [obj]: 0.8 Recall [subj]: 0.8