def __init__(self):
self.socling = SocioLinguistic()
self.features_list = []
self.features = {}
self.gettokens = Tokenizer()
class SocioLinguisticClassifier:
def __init__(self):
self.socling = SocioLinguistic()
self.features_list = []
self.features = {}
self.gettokens = Tokenizer()
def label_file_to_dict(self, filename):
dict_x = {}
for line in open(filename, "r"):
# print line
temp = line.split("||")
name = temp[0].strip()
label = temp[1].strip()
dict_x[name] = label
return dict_x
def get_features(self, line, demographic):
self.socling.sent = line
self.socling.sent_list = self.gettokens.tokenize(line.upper())
if demographic == "gend":
self.socling.single_exclam()
self.socling.pumping()
self.socling.agreement()
self.socling.affection()
self.socling.emoticons()
self.socling.excitement()
self.socling.ellipses()
self.socling.possessive_bigrams(self.features_list)
self.socling.laugh()
self.socling.shout()
self.socling.exasperation()
self.socling.honorifics()
self.socling.slang()
self.socling.pronouns()
def initialize(self,demographic):
self.features_list = set(self.socling.file_to_list("feature_files/feature_names_" + demographic))
def reset_dictionary(self):
self.features = {}
for feature in self.features_list:
self.features[feature] = 0
def stacked_socling_init(self,demographic):
self.features_list = set(self.socling.file_to_list("feature_files/feature_names_" + demographic))
self.reset_dictionary()
self.socling.features_dict = self.features