Tip Sentiment Analysis From The Yelp Phoenix Data Set

In this notebook we are going to analyze the tips the users have written after visiting a business and obtain the polarity of their opinions regarding the different products or items each business have to offer.

We will measure the polarity of the opinions about items by taking each sentence in the tip and tagging every word to identify whether its a nound, adjective, verb, adverb, etc. Once we have identified each word, for each noun in the sentence, we will take every adjective in the sentence, determine its polarity and calculate the polarity given to the noun in that sentence. In the following sections we are going to explain the details of how is this done.

Sentence tokenizer

The first step into this implementation of sentiment analysis of items is to take every tip and split it into sentences. Since each sentence expresses an idea, we are going to analyze each sentence separately. In python we can do this easily by using a tokenizer, for example:


In [5]:
import nltk
sentence_tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')
my_text = "The burgers are very good. The service is bad. They open untill very late and the drinks are quite expensive."
print('\n-----\n'.join(sentence_tokenizer.tokenize(my_text.strip())))


The burgers are very good.
-----
The service is bad.
-----
They open untill very late and the drinks are quite expensive.

Part of speech tagger

Now that we have separated each sentence, we can start to do part of speech tagging. To do this, we have to split each sentence into words and them tag those words. Thanks to NLTK this is also very straigthforward:


In [6]:
# Example
my_sentence = sentence_tokenizer.tokenize(my_text.strip())[0]
my_words = nltk.word_tokenize(my_sentence)
my_tagged_words = nltk.pos_tag(my_words)
print(my_tagged_words)

#Function
def tag_text(text):
    words = nltk.word_tokenize(text)
    tagged_words = nltk.pos_tag(words)
    return tagged_words


[('The', 'DT'), ('burgers', 'NNS'), ('are', 'VBP'), ('very', 'RB'), ('good', 'JJ'), ('.', '.')]

As you can see in the example above, the words are now tagged in a pair (word, tag). The meaning is the tags above is the following:

  • DT: Determiner.
  • NND: Plural noun.
  • VBP: Singular verb in present tense and non third person.
  • RB: Adverb.
  • JJ: Adjective.

There are much more tags, but for our analysis we just care for the nouns and the adjective. All the tags for nouns start with 'NN' and all the tags for adjectives start with 'JJ'.

Words polarity

The next step is to determine whether the adjectives that come along with the nouns are positive or negative. This will help us to determine how positive or negative is the review about the item (noun).

We can do this manually giving every word a score between [-1, 1]. For instance, awesome will be graded with 0.8, lousy -0.6, and so on.

Nevertheless, there is a database that contains the polarity of thousands of words in the english language. We can use this database instead and save us the work of grading all the words manually. The database can be found at http://sentiwordnet.isti.cnr.it/

Since the database is in a CSV file, we are going to have to parse it and store it in a friendly format we can use easily in python. In this case we will use a dictionary. The following function will enable us to do that.


In [7]:
# Created by
def load_sent_word_net():

    sent_scores = collections.defaultdict(list)

    with open("data/SentiWordNet_3.0.0_20130122.txt", "r") as csvfile:
        reader = csv.reader(csvfile, delimiter='\t', quotechar='"')
        for line in reader:
            if line[0].startswith("#"):
                continue
            if len(line) == 1:
                continue

            POS, ID, PosScore, NegScore, SynsetTerms, Gloss = line
            if len(POS) == 0 or len(ID) == 0:
                continue
            # print POS,PosScore,NegScore,SynsetTerms
            for term in SynsetTerms.split(" "):
                # drop #number at the end of every term
                term = term.split("#")[0]
                term = term.replace("-", " ").replace("_", " ")
                key = "%s/%s" % (POS, term.split("#")[0])
                sent_scores[key].append((float(PosScore), float(NegScore)))
    for key, value in sent_scores.iteritems():
        sent_scores[key] = numpy.mean(value, axis=0)

    return sent_scores

Now we can easily calculate the polarity of a word, to do that, we have defined the following function:


In [8]:
def calculate_word_score(tagged_word):

    word = tagged_word[0].lower()
    tag = tagged_word[1]

    if tag.startswith('JJ'):
        tag = 'a'
    else:
        return 0

    dict_word = tag + '/' + word
    total_score = 0

    if dict_word in sentiment_words:
        score = sentiment_words[dict_word]
        total_score = score[0] - score[1]

    return total_score

Feature extraction

To extract the features we have within the text, we use two patterns, the first pattern is, which we will call ANP is composed by {<JJ.>+<NN.>+}, that means one or more adjectives followed by one or more nouns, e.g., "hot dog". The second pattern is NP:{<NN.*>+} which is just one ore more nouns, e.g., "meat balls".

When we find a ANP pattern we will first evaluate if the first adjective that accompanies the words has a sentiment. If its a neutral word (like in "hot dog"), we state that the pattern we have found is a feature. On the other hand, if the adjective does have a sentiment (like in "great burger" or "bad root beer"), we remove it from the pattern and we will say that the remaining words are the feature.

Sentiment analysis

To analyze the sentiments associated to each feature we have several rules.

  • If there is a sentiment adjective immediately before the feature, we assign that sentiment to the feature.
  • If the above rule is not met, then we look for adjectives that are after the feature within the sentence and before another feature. The [beer is very good and the] fries are terrible. I had a [beer and a] delicious burger. In the previous examples, the braces are the context in which the algorithm will look for adjectives.
  • TODO: If the above rule is not met, we look for a sentiment verb before the feature, but not before the previos feature. I [loved the beer], [I also oredered french fries].
  • TODO: Negation words.
  • TODO: Look for patterns such as "glass of wine".
  • TODO: Count the number of times a feature and an adjective appear together in order to avoid assigning a false sentiment to that feature, for instance happy hour, black beans or sweet potato fries. If the word ‘hour’ is always accompanied by ‘happy’, then it must be a whole feature (‘happy hour’)
  • TODO: Stablish a hierarchy of features from general features that describe the place, to specific things. The main level can contain words like 'food', 'decoration', 'service', etc. Lower levels can include 'curry chicken', 'cheese burger', etc.
  • TODO: Filter out features that include a low rate of sentiment associated to them.

Note: Each feature will be assigned only one sentiment (1 for positive and -1 for negative), and it will be the sentiment of that is first found by evaluating the rules.

Results

The following are the features identified after running the program, each feature comes along with an array that cotains [positiveSentimentCount, negativeSentimentCount, featureCount] where featureCount is the number of times that the feature appears in the tips/reviews evaluated.

From tips of one restaurant

([1, 0, 2], u'lack')
([1, 0, 1], u'new patio')
([1, 0, 1], u'hummus..')
([1, 0, 6], u'tri')
([1, 0, 2], u'hour')
([1, 0, 1], u'happy hour specials-')
([1, 0, 4], u'drink speci')
([4, 0, 14], u'burger')
([1, 0, 2], u'friday')
([1, 0, 1], u'french fri')
([1, 0, 9], u'fez')
([1, 0, 1], u'today')
([3, 0, 12], u'fez burg')
([1, 0, 27], u'!')
([1, 0, 2], u'blackbean patti')
([1, 0, 5], u'cocktail')
([1, 0, 1], u'spot')
([1, 0, 1], u'caus')
([1, 0, 4], u'martini')
([8, 0, 12], u'food')
([1, 0, 1], u'promis')
([1, 0, 2], u'bar')
([1, 0, 1], u'choic')
([1, 0, 1], u'lot better tonight')
([1, 0, 1], u'thing')
([5, 0, 13], u'place')
([1, 0, 1], u'pomegranate margarita')
([1, 0, 1], u'accompani')
([1, 0, 1], u'chicken lettuce wrap')
([2, 0, 2], u'atmospher')
([1, 0, 1], u'greyhound')
([1, 0, 1], u'price')
([1, 0, 1], u'italo krisa')
([1, 0, 1], u'sun')
([1, 0, 1], u'chicken')
([1, 0, 1], u'staff')
([0, 1, 2], u'snack')
([1, 0, 1], u'hope')
([0, 1, 1], u'plate')
([1, 0, 8], u'get')
([2, 0, 3], u'potato fri')
([1, 1, 3], u'stuff')
([1, 0, 1], u'wonder')
([0, 1, 1], u'experi')
([1, 0, 1], u'everything look')
([2, 0, 3], u'hummus')
([1, 0, 1], u's')
([1, 0, 1], u'sammi')
([1, 0, 1], u'happy hour')
([2, 0, 10], u'fri')
([2, 0, 11], u'brunch')
([1, 0, 1], u'sound')
([4, 2, 11], u'servic')
([1, 0, 1], u'tall cup')
([1, 0, 1], u'entire menu')
([1, 0, 1], u'everyon')
([1, 0, 1], u'happy hour menu everyday')
([2, 1, 5], u'drink')
([0, 1, 1], u'tast')
([1, 0, 1], u'potato french fri')
([1, 0, 2], u'monika')
([0, 1, 1], u'lint rol')
([3, 0, 3], u'server')
([1, 0, 1], u'manag')
([0, 1, 1], u'bean burg')
([1, 0, 2], u'night')
([0, 1, 2], u'pasta')
([1, 0, 1], u'way')
([1, 0, 1], u'modern fun plac')
([1, 0, 1], u'rosemary chicken sandwich')
([0, 1, 1], u'large salad')
([2, 0, 6], u'time')

Top 10 count

Positive Negative Count Feature 1 0 27 u'!'
4 0 14 u'burger'
5 0 13 u'place'
3 0 12 u'fez burg'
8 0 12 u'food'
2 0 11 u'brunch'
4 2 11 u'servic'
2 0 10 u'fri'
1 0 9 u'fez'
1 0 8 u'get'

Top 10 positive

Positive Negative Count Feature 8 0 12 u'food'
5 0 13 u'place'
4 0 14 u'burger'
4 2 11 u'servic'
3 0 12 u'fez burg'
3 0 3 u'server'
2 0 11 u'brunch'
2 0 10 u'fri'
2 0 6 u'time'
2 1 5 u'drink'

Top 10 negative

4 2 11 u'servic'
2 1 5 u'drink'
1 1 3 u'stuff'
0 1 2 u'snack'
0 1 2 u'pasta'
0 1 1 u'plate'
0 1 1 u'experi'
0 1 1 u'tast'
0 1 1 u'lint rol'
0 1 1 u'bean burg'

From reviews of one restaurant

([0, 1, 1], u'uber modern decor')
([1, 0, 2], u'lord')
([0, 2, 2], u'bean veggie burg')
([0, 1, 1], u'lavish prais')
([2, 0, 16], u'bacon')
([0, 1, 1], u'dinner item')
([2, 1, 10], u'french fri')
([1, 0, 1], u'happy hour spot')
([1, 0, 1], u'little plac')
([0, 1, 1], u'3rd st.')
([12, 2, 26], u'music')
([4, 0, 6], u'chicken sandwich')
([3, 1, 20], u'glass')
([1, 0, 1], u'burger shop')
([0, 1, 3], u'bit slow')
([3, 0, 30], u'wine')
([1, 0, 1], u'feedback')
([1, 0, 3], u'fix')
([1, 0, 2], u'pomegranate martini')
([1, 0, 1], u'lot better tonight')
([0, 1, 1], u'spicy powd')
([0, 1, 7], u'tangi')
([0, 1, 2], u'extensive martini list')
([1, 0, 1], u'white')
([0, 1, 1], u'letter')
([1, 0, 1], u'goodbye lunch')
([0, 1, 2], u'hospit')
([2, 0, 12], u'balsamic burg')
([1, 0, 1], u'burger (')
([1, 0, 2], u'caper')
([0, 1, 2], u'layout')
([0, 1, 1], u'lounge mus')
([1, 0, 1], u'arroz con pollo')
([18, 2, 160], u'menu')
([14, 6, 136], u'restaur')
([6, 3, 35], u'plate')
([1, 0, 12], u'pomegran')
([3, 0, 36], u'sauc')
([1, 0, 4], u'result')
([1, 0, 1], u'figur')
([0, 1, 1], u'big group')
([0, 1, 7], u'pita')
([0, 1, 1], u'phoenix vacay')
([23, 5, 167], u'fri')
([0, 1, 20], u'life')
([0, 1, 1], u'worker')
([1, 0, 2], u'duck breast')
([1, 0, 1], u'chili')
([1, 0, 1], u'spin')
([2, 0, 3], u'marriag')
([0, 1, 1], u'draft list')
([1, 0, 2], u'mushroom risotto')
([0, 1, 1], u'experience w/a')
([1, 0, 1], u'huge port')
([0, 1, 1], u'pesto sound')
([1, 0, 1], u'had')
([2, 1, 14], u'right')
([6, 0, 23], u'crowd')
([1, 0, 1], u'vibe patio')
([2, 1, 24], u'fez salad')
([3, 0, 9], u'flatbread')
([1, 0, 1], u'( check')
([1, 0, 5], u'son')
([0, 1, 6], u'wrap')
([1, 0, 15], u'happi')
([1, 0, 1], u'g-spot cocktail')
([1, 0, 1], u'green stool')
([0, 1, 1], u'cheese/balsamic burg')
([1, 0, 1], u'burgers entre')
([1, 0, 1], u'chicken sandwhich')
([1, 0, 1], u'intens')
([39, 5, 256], u'time')
([0, 1, 2], u'pen')
([3, 0, 7], u'decis')
([1, 0, 4], u'scottsdal')
([1, 0, 1], u'chibatta bread')
([0, 1, 1], u'cooki')
([1, 0, 1], u'vodka svedka')
([1, 0, 1], u'minion')
([1, 1, 4], u'sign')
([0, 7, 7], u'cheese burg')
([1, 0, 12], u'feta chees')
([1, 0, 1], u'urban hip vib')
([1, 0, 2], u'lemon caper talapia')
([1, 0, 25], u'love')
([1, 1, 4], u'strawberry/blueberry cashew salad')
([1, 0, 4], u'bloodi')
([8, 8, 115], u'peopl')
([2, 0, 6], u'whatev')
([1, 0, 1], u'house chardonnay')
([9, 2, 42], u'spot')
([2, 2, 20], u'date')
([1, 0, 1], u'own music sensation monika')
([0, 1, 1], u'crazy ingredi')
([1, 0, 1], u'dirty martini -cool')
([1, 0, 1], u'parade rout')
([1, 0, 1], u'enough uniqu')
([2, 1, 19], u'one')
([2, 0, 13], u'bite')
([1, 0, 2], u'rival')
([1, 0, 4], u'greyhound')
([0, 1, 2], u'sat')
([1, 4, 41], u'noth')
([1, 0, 1], u'bruchetta appet')
([8, 10, 82], u'review')
([1, 0, 1], u'tasting hamburg')
([1, 0, 1], u'next refil')
([0, 1, 1], u'table receipt')
([0, 1, 1], u'spark')
([0, 1, 2], u'stretch')
([4, 0, 26], u'lamb kisra')
([1, 0, 1], u'light decad')
([1, 0, 14], u'hubbi')
([1, 0, 1], u'earlier thought')
([1, 0, 2], u'saving grac')
([3, 0, 3], u'outdoor patio')
([0, 1, 5], u'summer')
([1, 0, 1], u'darn')
([1, 1, 35], u'manag')
([0, 1, 1], u'medierranne good')
([1, 0, 3], u'apricot glaz')
([1, 0, 1], u'handshak')
([3, 5, 57], u'side')
([4, 0, 20], u'rosemary fri')
([1, 1, 12], u'bottl')
([0, 1, 3], u'dirti')
([0, 1, 1], u')
dessert')
([1, 0, 7], u'am')
([1, 0, 1], u'tasting sandwich')
([1, 0, 1], u'berry shortcak')
([1, 0, 1], u'glass door')
([1, 0, 1], u'little nam')
([0, 1, 1], u'past')
([1, 0, 1], u'sexy boy')
([1, 0, 2], u'section')
([1, 0, 1], u'holiday misfit')
([0, 1, 5], u'situat')
([1, 0, 1], u'little patio')
([1, 0, 1], u'luck')
([9, 0, 21], u'select')
([1, 0, 9], u'morn')
([1, 0, 16], u'door')
([5, 0, 13], u'compani')
([0, 1, 4], u'salti')
([2, 0, 12], u'dress')
([1, 0, 1], u')
aroma')
([3, 0, 13], u'waitstaff')
([6, 0, 49], u'patio')
([1, 0, 2], u'price point')
([1, 0, 84], u'tri')
([1, 0, 5], u'egg white omelet')
([1, 0, 3], u'crisp pomegranate chicken')
([6, 0, 30], u'rosemary chicken sandwich')
([3, 0, 11], u'customer servic')
([1, 0, 1], u'candlelight')
([1, 0, 8], u'number')
([0, 1, 4], u'guest')
([1, 0, 3], u'mmmm')
([0, 1, 1], u'burrito')
([1, 0, 1], u'tummi')
([5, 0, 49], u'pear')
([0, 1, 2], u'burger plac')
([1, 0, 2], u'half hour')
([1, 0, 1], u'food sound')
([1, 0, 1], u')
fez')
([1, 0, 1], u'garlic on')
([1, 0, 1], u'cuh-razy crazi')
([1, 0, 2], u'gooey')
([1, 0, 1], u'factor')
([0, 1, 1], u'weeks-')
([2, 0, 5], u'set')
([1, 0, 12], u'see')
([1, 0, 1], u'sec')
([2, 0, 3], u'compliment')
([0, 1, 1], u'bean patti')
([1, 0, 1], u'krisa')
([0, 1, 1], u'brunch food')
([0, 2, 9], u'patti')
([1, 0, 1], u'modern')
([1, 0, 1], u'mediterranean flair')
([1, 0, 5], u'hostess')
([13, 0, 55], u'decor')
([1, 0, 1], u'guest room')
([0, 1, 10], u'opinion')
([0, 2, 11], u'person')
([1, 0, 1], u'cheddar')
([1, 0, 1], u'potatoes on')
([0, 1, 1], u'encount')
([1, 0, 1], u'atmosphere food')
([1, 0, 1], u'irrit')
([1, 0, 13], u'custom')
([1, 0, 3], u'up')
([1, 0, 1], u'african pepp')
([0, 1, 3], u'land')
([1, 0, 1], u'first go')
([1, 0, 3], u'freakin')
([0, 1, 1], u'music ( taylor swfit techno remix')
([1, 0, 5], u'sens')
([1, 0, 2], u'vegetarian burg')
([1, 0, 8], u'right amount')
([1, 0, 3], u'recip')
([1, 0, 1], u'cool tabl')
([0, 2, 7], u'doubt')
([1, 0, 3], u'big salad')
([0, 1, 6], u'babi')
([1, 0, 3], u'pepper aioli')
([1, 0, 1], u'dream goin')
([2, 0, 3], u'kisra bread')
([1, 0, 1], u'beef patti')
([3, 0, 30], u'lamb')
([1, 2, 3], u'watermelon')
([1, 0, 21], u'perfect')
([3, 3, 75], u'bar')
([0, 1, 1], u'realize')
([1, 0, 1], u'little bar')
([0, 1, 1], u'east villag')
([1, 0, 1], u'lighting insid')
([1, 0, 1], u'server lauren')
([0, 1, 1], u'embarrass')
([2, 0, 4], u'outsid')
([2, 1, 15], u'veggi')
([1, 0, 12], u'owner')
([4, 0, 14], u'pomegranate margarita')
([6, 0, 30], u'bartend')
([0, 1, 1], u'fancy burger bar')
([1, 0, 1], u'squash pasta')
([0, 1, 1], u'steep')
([2, 0, 2], u'hot dog')
([1, 0, 17], u'face')
([0, 1, 1], u'great review')
([1, 0, 1], u'perfect port')
([1, 0, 2], u'jar')
([1, 0, 4], u'half siz')
([1, 0, 1], u'gestur')
([1, 0, 1], u'first cute boy')
([1, 0, 1], u'sinus')
([2, 0, 11], u'spicy harissa fri')
([6, 3, 18], u'stuff')
([1, 0, 2], u'fez frittata')
([1, 0, 2], u'fresh food')
([1, 0, 1], u'old facebook')
([1, 0, 1], u'least food')
([1, 0, 2], u'strawberry blueberry cashew salad -it')
([0, 1, 1], u'bye bye fez')
([1, 0, 1], u'apricot martinis- check lush cherry martinis- check juici')
([0, 1, 1], u'get togeth')
([57, 5, 264], u'drink')
([1, 0, 3], u'exampl')
([1, 1, 13], u'crisp')
([1, 0, 1], u'pre-dinner cocktail')
([1, 0, 24], u'onion')
([2, 7, 55], u'anyth')
([1, 0, 2], u'garlicki')
([0, 1, 1], u'old lady girlfriend')
([0, 1, 5], u'excellent servic')
([2, 0, 7], u'clientel')
([1, 0, 2], u'specific dish')
([1, 0, 1], u'potato fry junki')
([1, 0, 2], u'all american burg')
([1, 1, 7], u'large group')
([1, 0, 1], u'sirloin')
([1, 0, 3], u'nonetheless')
([1, 0, 1], u'glance insid')
([1, 0, 1], u'fufu drink')
([0, 1, 1], u'vermouth')
([1, 0, 3], u'duxell')
([1, 0, 6], u'lack')
([0, 1, 4], u'one els')
([1, 0, 1], u'fish cake-')
([2, 0, 8], u'chef')
([2, 0, 7], u'garlic hummus')
([1, 0, 7], u'smoke')
([1, 0, 8], u'downtown phoenix')
([0, 1, 1], u'reign')
([0, 1, 1], u'hand am')
([1, 2, 21], u'word')
([2, 1, 23], u'work')
([1, 0, 1], u'tan-tan chicken sandwich crispy panko chicken breast')
([2, 0, 23], u'pizza')
([0, 1, 1], u'chili burg')
([1, 0, 11], u'green')
([2, 0, 104], u'order')
([2, 0, 4], u'savori')
([1, 0, 1], u'must tri')
([0, 1, 1], u'girl friend')
([5, 1, 36], u'bread')
([0, 1, 1], u'standard')
([1, 0, 1], u'great peopl')
([1, 0, 1], u'airi')
([1, 0, 1], u'happy drink')
([4, 1, 17], u'ciabatta bread')
([1, 0, 1], u'target')
([1, 0, 1], u'peppers folk')
([1, 0, 61], u'minut')
([1, 0, 1], u'flavor great bun')
([0, 1, 1], u'various green')
([1, 0, 1], u'opposit')
([0, 1, 1], u'toast')
([1, 0, 1], u'food opt')
([1, 0, 1], u'potato fries- y')
([2, 0, 9], u'steak')
([1, 0, 1], u'balsamic vari')
([1, 0, 4], u'gentleman')
([0, 1, 1], u'svedka martini')
([1, 0, 1], u'raspberry spinach salad')
([1, 0, 14], u'kitchen')
([22, 2, 85], u'hummus')
([0, 1, 1], u'eyesight')
([0, 1, 1], u'tone')
([1, 0, 2], u'gay wait')
([4, 0, 6], u'chocolate mouss')
([0, 1, 4], u'air')
([1, 0, 1], u'server bryan')
([2, 0, 5], u'pita bread')
([1, 0, 1], u'buy-one-get-one-free margarita')
([1, 0, 1], u'hang')
([0, 6, 22], u'hand')
([1, 0, 1], u'kisba')
([5, 7, 75], u'night')
([0, 1, 1], u'seasoned.the lamb slid')
([1, 0, 1], u'greek phyllo pastri')
([1, 0, 1], u'daily drink speci')
([0, 1, 1], u'bean burger patti')
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([1, 0, 5], u'central avenu')
([2, 2, 73], u'phoenix')
([1, 0, 1], u'kisra appet')
([1, 0, 1], u'consid')
([2, 0, 9], u'apricot salmon')
([0, 1, 1], u'overtness issu')
([1, 0, 1], u'valentin')
([1, 0, 1], u'whenever anyon')
([1, 0, 29], u'water')
([3, 0, 9], u'french toast')
([4, 1, 50], u'cinnamon')
([1, 0, 3], u'concoct')
([1, 0, 1], u'freezing air')
([0, 1, 3], u'loung')
([1, 0, 19], u'last tim')
([1, 0, 24], u'today')
([2, 0, 2], u'cowboy')
([0, 1, 1], u'purpos')
([1, 0, 2], u'surround')
([0, 1, 8], u'harissa')
([0, 1, 1], u'construction zon')
([4, 0, 32], u'cocktail')
([5, 1, 18], u'combin')
([0, 1, 2], u'half vers')
([0, 1, 1], u'special dipping sauc')
([4, 0, 30], u'name')
([0, 1, 1], u'pasta rock')
([1, 0, 1], u'paprika aioli')
([1, 0, 1], u'background fez')
([1, 0, 1], u'side dish')
([1, 0, 4], u'turn')
([73, 12, 451], u'place')
([1, 0, 1], u'unique light fixtur')
([0, 1, 1], u'zombie drink')
([1, 0, 1], u'oh em gee-hand')
([1, 0, 1], u'hub')
([1, 0, 2], u'season')
([1, 0, 2], u'huh')
([2, 0, 3], u'balanc')
([0, 1, 3], u'quantiti')
([0, 1, 11], u'yelper')
([0, 1, 4], u'cheap')
([2, 0, 9], u'fez benedict')
([20, 1, 92], u')
')
([1, 0, 1], u'prefer plac')
([1, 0, 1], u'last fez burg')
([1, 0, 1], u'everything look')
([1, 0, 1], u'berri')
([0, 1, 2], u'pop')
([0, 2, 35], u'coupl')
([1, 0, 1], u'tasteless')
([0, 1, 4], u'spirit')
([0, 1, 1], u'best burg')
([1, 0, 1], u'cabbage coleslaw')
([1, 0, 7], u'trip')
([2, 0, 3], u'gourmet burg')
([0, 1, 1], u'handsom')
([2, 0, 2], u'potato french fri')
([0, 1, 3], u'kill')
([1, 0, 1], u'happy hour list look')
([1, 0, 1], u'everything tast')
([1, 1, 8], u'slice')
([2, 0, 17], u'mood')
([0, 1, 2], u'moon')
([1, 0, 39], u'ok')
([2, 0, 52], u'oh')
([1, 0, 18], u'shrimp')
([8, 1, 31], u'veggie burg')
([1, 0, 1], u'little laid-back plac')
([1, 0, 1], u'banana split martini')
([1, 0, 1], u'most talented actor/waiter/dad alway')
([1, 0, 24], u'wife')
([1, 0, 2], u'recession pl')
([7, 6, 29], u'dish')
([1, 0, 3], u'woman')
([1, 0, 1], u'brunch cocktail')
([1, 0, 1], u'forgot-to-make-reserv')
([2, 1, 13], u'tea')
([1, 0, 3], u'design')
([1, 0, 1], u'season veget')
([0, 1, 5], u'sun')
([1, 0, 6], u'version')
([1, 0, 1], u'kisia')
([3, 0, 11], u'bloody mari')
([1, 0, 1], u'fishcak')
([1, 1, 32], u'cours')
([6, 2, 51], u'sandwich')
([2, 0, 2], u'potato fez fri')
([1, 0, 1], u'looking guy')
([5, 0, 13], u'dipping sauc')
([1, 0, 2], u'cook')
([1, 0, 7], u'style')
([1, 0, 1], u'somebodi')
([1, 0, 2], u'traditional burg')
([1, 0, 2], u'friendship')
([1, 0, 1], u'thing..')
([1, 0, 1], u'sit-down dinn')
([5, 0, 16], u'feel')
([1, 0, 6], u'bland')
([4, 2, 18], u'option')
([1, 1, 32], u'kind')
([1, 0, 1], u'5-star')
([49, 4, 98], u'atmospher')
([1, 0, 1], u'work happy hour food-')
([1, 0, 1], u'horseradish )
')
([0, 1, 1], u'long stori')
([1, 0, 2], u'fantastic food')
([2, 0, 35], u'hip')
([0, 1, 1], u'last supp')
([0, 1, 1], u'misstep')
([1, 0, 1], u'flier')
([1, 0, 6], u'crispi')
([1, 0, 4], u'same th')
([0, 1, 1], u'lemon flavour')
([1, 0, 2], u'own way')
([1, 0, 8], u'kick')
([0, 1, 1], u'check east coast vibe- check great bartenders- check clean')
([1, 0, 1], u'champagne glass')
([1, 0, 5], u'rim')
([1, 0, 2], u'shirt')
([1, 0, 1], u'balsamic fez burg')
([0, 15, 20], u'chees')
([0, 1, 1], u'pyllo pocket')
([1, 0, 2], u'move')
([1, 0, 4], u'ciabatta bun')
([2, 1, 5], u'caesar salad')
([7, 0, 11], u'surpris')
([0, 1, 2], u'masterpiec')
([1, 0, 1], u'fair fri')
([1, 0, 1], u'signature cocktail')
([1, 0, 7], u'angus burg')
([1, 0, 1], u'daaaaang')
([1, 0, 1], u'z')
([1, 0, 4], u'peach bellini')
([1, 0, 1], u'thing mom')
([11, 1, 20], u'drink speci')
([0, 1, 8], u'fez lettuce wrap')
([1, 0, 9], u'folk')
([1, 0, 14], u'fine')
([1, 0, 2], u'sexi')
([1, 0, 1], u'egg omelett')
([0, 1, 1], u'simple side salad')
([2, 0, 4], u'water glass')
([1, 0, 1], u'semi-dark atmospher')
([1, 0, 16], u'app')
([12, 2, 46], u'egg')
([1, 0, 1], u'use')
([1, 0, 1], u'music volum')
([0, 1, 1], u'old gray')
([0, 1, 30], u'sort')
([2, 0, 5], u'impress')
([0, 1, 1], u'strawberry/blueberry hafl salad')
([1, 1, 10], u'tap')
([0, 3, 17], u'patron')
([1, 0, 3], u'tad')
([2, 0, 4], u'carrot')
([1, 0, 7], u'sit')
([0, 1, 1], u'black bean burg')
([0, 1, 2], u'attend')
([0, 1, 1], u'play someth')
([1, 0, 13], u'attent')
([3, 2, 11], u'light')
([1, 0, 1], u'pita jungl')
([0, 1, 1], u'rainy gloomi')
([5, 1, 61], u'martini')
([1, 0, 1], u'bye')
([1, 0, 1], u'nite-o-drinkin')
([1, 0, 9], u'cheesecak')
([2, 0, 6], u'slow servic')
([1, 0, 2], u'romain')
([1, 0, 7], u'drink menu')
([1, 0, 1], u'littttlee')
([1, 0, 1], u'accent')
([1, 0, 5], u'french bread')
([1, 0, 2], u'their')
([0, 1, 6], u'chicken lettuce wrap')
([1, 0, 1], u'spinach gyro flatbread pizza')
([1, 0, 1], u'potato fries everyone laud')
([0, 1, 1], u'toilet pap')
([1, 0, 2], u'personal pizza')
([5, 3, 29], u'chicken')
([0, 1, 1], u'feat')
([12, 1, 26], u'locat')
([1, 0, 8], u'eat')
([2, 0, 7], u'combo')
([0, 1, 1], u'spud')
([1, 0, 1], u'breakfast kisra bread')
([1, 0, 2], u'view')
([1, 0, 2], u'knowledg')
([1, 0, 1], u'potato fi')
([1, 0, 1], u'potatoe fries everyon')
([2, 0, 2], u'joy')
([0, 1, 3], u'background mus')
([4, 0, 6], u'job')
([1, 0, 1], u'sunday brunch menu')
([2, 0, 5], u'addit')
([0, 1, 6], u'walk')
([1, 0, 1], u'amigo')
([0, 1, 5], u'bbq')
([0, 1, 5], u'present')
([1, 0, 3], u'vanilla')
([3, 1, 17], u'tangier burg')
([0, 1, 1], u'fling')
([1, 0, 1], u'real nice ladi')
([1, 0, 1], u'buddy robert m.')
([1, 0, 1], u'intriguing menu item')
([0, 1, 1], u'same compani')
([1, 0, 18], u'other')
([1, 0, 1], u'myth')
([3, 1, 20], u'side salad')
([0, 1, 1], u'amazing th')
([1, 0, 5], u'candac')
([1, 0, 1], u'church')
([1, 0, 4], u'chilean sea bass')
([1, 0, 1], u'belt bucklet')
([0, 13, 13], u'bean burg')
([0, 4, 13], u'pasta')
([1, 0, 1], u'biscuit')
([4, 0, 5], u'weather')
([1, 0, 2], u'modern feel')
([1, 0, 1], u'looking peopl')
([0, 1, 4], u'temp')
([1, 0, 3], u'gspot')
([1, 0, 1], u'own fez saw someth')
([1, 0, 1], u'potato/garlic fri')
([1, 0, 6], u'kinda')
([0, 1, 1], u'light rail construction period')
([1, 0, 1], u'white pl')

Top 10 Count

Positive Negative Count Feature 23 1 627 u'fez'
200 10 565 u'food'
73 12 451 u'place'
130 38 360 u'servic'
83 7 305 u'burger'
57 5 264 u'drink'
39 5 256 u'time'
10 6 195 u'friend'
188 0 190 u'potato fri'
23 5 167 u'fri'

Top 10 Positive

Positive Negative Count Feature 200 10 565 u'food'
188 0 190 u'potato fri'
130 38 360 u'servic'
83 7 305 u'burger'
73 12 451 u'place'
57 5 264 u'drink'
49 4 98 u'atmospher'
41 0 61 u'hour'
39 5 256 u'time'
30 4 75 u'price'

Top 10 Negative

130 38 360 u'servic'
0 15 20 u'chees'
0 13 13 u'bean burg'
73 12 451 u'place'
28 11 84 u'experi'
200 10 565 u'food'
17 10 82 u'thing'
8 10 82 u'review'
8 8 115 u'peopl'
3 8 77 u'day'