diff --git a/data/emojis.json b/data/emojis.json
new file mode 100644
index 0000000..1c68546
--- /dev/null
+++ b/data/emojis.json
@@ -0,0 +1,116 @@
+{
+	"😀" : 0.5,
+	"😁" : 0.8,
+	"😂" : 1.0,
+	"🤣" : 1.0,
+	"😃" : 0.8,
+	"😄" : 1.0,
+	"😅" : 1.0,
+	"😆" : 1.0,
+	"😉" : 0.5,
+	"😊" : 0.3,
+	"😋" : 0.4,
+	"😎" : 0.5,
+	"😍" : 1.0,
+	"😘" : 1.0,
+	"😗" : 0.8,
+	"😙" : 1.0,
+	"😚" : 1.0,
+	"☺" : 0.3,
+	"🙂" : 0.3,
+	"🤗" : 0.6,
+	"🤩" : 1.0,
+	"🤔" : 0.0,
+	"🤨" : -0.2,
+	"😐" : 0.0,
+	"😑" : -0.2,
+	"😶" : 0.0,
+	"🙄" : 0.0,
+	"😏" : 0.3,
+	"😣" : -1.0,
+	"😥" : -1.0,
+	"😮" : 0.0,
+	"🤐" : 0.0,
+	"😯" : 0.0,
+	"😪" : -1.0,
+	"😫" : -1.0,
+	"😴" : 0.0,
+	"😌" : 0.2,
+	"😛" : 0.7,
+	"😜" : 0.8,
+	"😝" : 1.0,
+	"🤤" : 0.8,
+	"😒" : -0.5,
+	"😓" : -0.8,
+	"😔" : -0.5,
+	"😕" : -0.3,
+	"🙃" : 0.5,
+	"🤑" : 1.0,
+	"😲" : 0.0,
+	"☹" : -0.8,
+	"🙁" : -0.6,
+	"😖" : -1.0,
+	"😞" : -0.6,
+	"😟" : -0.6,
+	"😤" : -0.7,
+	"😢" : -0.8,
+	"😭" : -1.0,
+	"😦" : -0.6,
+	"😧" : -0.6,
+	"😨" : -0.7,
+	"😩" : -0.8,
+	"🤯" : -1.0,
+	"😬" : -0.5,
+	"😰" : -0.8,
+	"😱" : -1.0,
+	"😳" : 0.0,
+	"🤪" : 1.0,
+	"😵" : -0.4,
+	"😡" : -0.9,
+	"😠" : -0.8,
+	"🤬" : -1.0,
+	"😷" : 0.0,
+	"🤒" : -0.8,
+	"🤕" : -0.8,
+	"🤢" : -0.9,
+	"🤮" : -1.0,
+	"🤧" : -0.8,
+	"😇" : 0.8,
+	"🤠" : 0.7,
+	"🤡" : 0.8,
+	"🤥" : -0.6,
+	"🤫" : 0.0,
+	"🤭" : 0.2,
+	"🧐" : 0.0,
+	"🤓" : 0.5,
+	"💪" : 1.0,
+	"👈" : 0.0,
+	"👉" : 0.0,
+	"☝" : 1.0,
+	"👆" : 1.0,
+	"🖕" : -1.0,
+	"👇" : -1.0,
+	"✌" : 1.0,
+	"🤞" : 0.0,
+	"🖖" : 0.0,
+	"🤘" : 1.0,
+	"🖐" : 0.0,
+	"✋" : 0.0,
+	"👌" : 1.0,
+	"👍" : 1.0,
+	"👎" : -1.0,
+	"✊" : 1.0,
+	"👊" : 1.0,
+	"🤛" : 0.0,
+	"🤜" : 0.0,
+	"🤚" : 0.0,
+	"👋" : 0.0,
+	"🤟" : 1.0,
+	"✍" : 0.0,
+	"👏" : 1.0,
+	"👐" : 0.0,
+	"🙌" : 1.0,
+	"🤲" : 0.0,
+	"🙏" : 1.0,
+	"🤝" : 1.0
+}
\ No newline at end of file
diff --git a/lib/sentimental.rb b/lib/sentimental.rb
index 9c20be9..728d8e2 100644
--- a/lib/sentimental.rb
+++ b/lib/sentimental.rb
@@ -25,6 +25,20 @@ def score(string)
     end[:score]
   end
 
+  def score_average(string)
+    return 0 if neutral_regexps.any? { |regexp| string =~ regexp }
+
+    initial_scoring = {score: 0, current_influencer: 1.0}
+    word_counter    = 0
+
+    w = extract_words_with_n_grams(string).inject(initial_scoring) do |current_scoring, word|
+      word_counter += 1
+      process_word(current_scoring, word)
+    end
+
+    w[:score].to_f / word_counter.to_f
+  end
+
   def sentiment(string)
     score = score(string)
 
@@ -42,7 +56,7 @@ def classify(string)
   end
 
   def load_defaults
-    %w(slang en_words).each do |filename|
+    %w(slang en_words emojis).each do |filename|
       load_from_json(File.dirname(__FILE__) + "/../data/#{filename}.json")
     end
     load_influencers_from_json(File.dirname(__FILE__) + '/../data/influencers.json')
@@ -86,11 +100,12 @@ def process_word(scoring, word)
   end
 
   def extract_words(string)
-    string.to_s.downcase.scan(/([\w']+|\S{2,})/).flatten
+    string.to_s.downcase.scan(/([\w']+|\S{2,}+|[\u{00A9}\u{00AE}\u{203C}\u{2049}\u{2122}\u{2139}\u{2194}-\u{2199}\u{21A9}-\u{21AA}\u{231A}-\u{231B}\u{2328}\u{23CF}\u{23E9}-\u{23F3}\u{23F8}-\u{23FA}\u{24C2}\u{25AA}-\u{25AB}\u{25B6}\u{25C0}\u{25FB}-\u{25FE}\u{2600}-\u{2604}\u{260E}\u{2611}\u{2614}-\u{2615}\u{2618}\u{261D}\u{2620}\u{2622}-\u{2623}\u{2626}\u{262A}\u{262E}-\u{262F}\u{2638}-\u{263A}\u{2640}\u{2642}\u{2648}-\u{2653}\u{2660}\u{2663}\u{2665}-\u{2666}\u{2668}\u{267B}\u{267F}\u{2692}-\u{2697}\u{2699}\u{269B}-\u{269C}\u{26A0}-\u{26A1}\u{26AA}-\u{26AB}\u{26B0}-\u{26B1}\u{26BD}-\u{26BE}\u{26C4}-\u{26C5}\u{26C8}\u{26CE}-\u{26CF}\u{26D1}\u{26D3}-\u{26D4}\u{26E9}-\u{26EA}\u{26F0}-\u{26F5}\u{26F7}-\u{26FA}\u{26FD}\u{2702}\u{2705}\u{2708}-\u{270D}\u{270F}\u{2712}\u{2714}\u{2716}\u{271D}\u{2721}\u{2728}\u{2733}-\u{2734}\u{2744}\u{2747}\u{274C}\u{274E}\u{2753}-\u{2755}\u{2757}\u{2763}-\u{2764}\u{2795}-\u{2797}\u{27A1}\u{27B0}\u{27BF}\u{2934}-\u{2935}\u{2B05}-\u{2B07}\u{2B1B}-\u{2B1C}\u{2B50}\u{2B55}\u{3030}\u{303D}\u{3297}\u{3299}\u{1F004}\u{1F0CF}\u{1F170}-\u{1F171}\u{1F17E}-\u{1F17F}\u{1F18E}\u{1F191}-\u{1F19A}\u{1F1E6}-\u{1F1FF}\u{1F201}-\u{1F202}\u{1F21A}\u{1F22F}\u{1F232}-\u{1F23A}\u{1F250}-\u{1F251}\u{1F300}-\u{1F321}\u{1F324}-\u{1F393}\u{1F396}-\u{1F397}\u{1F399}-\u{1F39B}\u{1F39E}-\u{1F3F0}\u{1F3F3}-\u{1F3F5}\u{1F3F7}-\u{1F4FD}\u{1F4FF}-\u{1F53D}\u{1F549}-\u{1F54E}\u{1F550}-\u{1F567}\u{1F56F}-\u{1F570}\u{1F573}-\u{1F57A}\u{1F587}\u{1F58A}-\u{1F58D}\u{1F590}\u{1F595}-\u{1F596}\u{1F5A4}-\u{1F5A5}\u{1F5A8}\u{1F5B1}-\u{1F5B2}\u{1F5BC}\u{1F5C2}-\u{1F5C4}\u{1F5D1}-\u{1F5D3}\u{1F5DC}-\u{1F5DE}\u{1F5E1}\u{1F5E3}\u{1F5E8}\u{1F5EF}\u{1F5F3}\u{1F5FA}-\u{1F64F}\u{1F680}-\u{1F6C5}\u{1F6CB}-\u{1F6D2}\u{1F6E0}-\u{1F6E5}\u{1F6E9}\u{1F6EB}-\u{1F6EC}\u{1F6F0}\u{1F6F3}-\u{1F6F8}\u{1F910}-\u{1F93A}\u{1F93C}-\u{1F93E}\u{1F940}-\u{1F945}\u{1F947}-\u{1F94C}\u{1F950}-\u{1F96B}\u{1F980}-\u{1F997}\u{1F9C0}\u{1F9D0}-\u{1F9E6}\u{200D}\u{20E3}\u{FE0F}\u{E0020}-\u{E007F}\u{2388}\u{2605}\u{2607}-\u{260D}\u{260F}-\u{2610}\u{2612}\u{2616}-\u{2617}\u{2619}-\u{261C}\u{261E}-\u{261F}\u{2621}\u{2624}-\u{2625}\u{2627}-\u{2629}\u{262B}-\u{262D}\u{2630}-\u{2637}\u{263B}-\u{263F}\u{2641}\u{2643}-\u{2647}\u{2654}-\u{265F}\u{2661}-\u{2662}\u{2664}\u{2667}\u{2669}-\u{267A}\u{267C}-\u{267E}\u{2680}-\u{2691}\u{2698}\u{269A}\u{269D}-\u{269F}\u{26A2}-\u{26A9}\u{26AC}-\u{26AF}\u{26B2}-\u{26BC}\u{26BF}-\u{26C3}\u{26C6}-\u{26C7}\u{26C9}-\u{26CD}\u{26D0}\u{26D2}\u{26D5}-\u{26E8}\u{26EB}-\u{26EF}\u{26F6}\u{26FB}-\u{26FC}\u{26FE}-\u{2701}\u{2703}-\u{2704}\u{270E}\u{2710}-\u{2711}\u{2765}-\u{2767}\u{1F000}-\u{1F003}\u{1F005}-\u{1F0CE}\u{1F0D0}-\u{1F0FF}\u{1F10D}-\u{1F10F}\u{1F12F}\u{1F16C}-\u{1F16F}\u{1F1AD}-\u{1F1E5}\u{1F203}-\u{1F20F}\u{1F23C}-\u{1F23F}\u{1F249}-\u{1F24F}\u{1F252}-\u{1F2FF}\u{1F322}-\u{1F323}\u{1F394}-\u{1F395}\u{1F398}\u{1F39C}-\u{1F39D}\u{1F3F1}-\u{1F3F2}\u{1F3F6}\u{1F4FE}\u{1F53E}-\u{1F548}\u{1F54F}\u{1F568}-\u{1F56E}\u{1F571}-\u{1F572}\u{1F57B}-\u{1F586}\u{1F588}-\u{1F589}\u{1F58E}-\u{1F58F}\u{1F591}-\u{1F594}\u{1F597}-\u{1F5A3}\u{1F5A6}-\u{1F5A7}\u{1F5A9}-\u{1F5B0}\u{1F5B3}-\u{1F5BB}\u{1F5BD}-\u{1F5C1}\u{1F5C5}-\u{1F5D0}\u{1F5D4}-\u{1F5DB}\u{1F5DF}-\u{1F5E0}\u{1F5E2}\u{1F5E4}-\u{1F5E7}\u{1F5E9}-\u{1F5EE}\u{1F5F0}-\u{1F5F2}\u{1F5F4}-\u{1F5F9}\u{1F6C6}-\u{1F6CA}\u{1F6D3}-\u{1F6DF}\u{1F6E6}-\u{1F6E8}\u{1F6EA}\u{1F6ED}-\u{1F6EF}\u{1F6F1}-\u{1F6F2}\u{1F6F9}-\u{1F6FF}\u{1F774}-\u{1F77F}\u{1F7D5}-\u{1F7FF}\u{1F80C}-\u{1F80F}\u{1F848}-\u{1F84F}\u{1F85A}-\u{1F85F}\u{1F888}-\u{1F88F}\u{1F8AE}-\u{1F90F}\u{1F93F}\u{1F94D}-\u{1F94F}\u{1F96C}-\u{1F97F}\u{1F998}-\u{1F9BF}\u{1F9C1}-\u{1F9CF}])/).flatten
   end
 
   def extract_words_with_n_grams(string)
     words = extract_words(string)
+
     (1..ngrams).to_a.map do |ngram_size|
       ngramify(words, ngram_size)
     end.flatten