a method’s result varies when it is tested for different social media sources.

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  **Dataset**              **Messages**   **Positives**   **Negatives**   **Neutrals**          
  ------------------------ -------------- --------------- --------------- -------------- ------ -------
  Sentistrength\_bbc       1,000          99              653             248            3.98   64.39
  Sentistrength\_digg      1,077          210             572             295            2.50   33.97
  Vader\_nyt               5,190          2,204           2,742           244            1.01   17.76
  Nikolaos\_ted            839            318             409             112            1      16.95
  Sentistrength\_youtube   3,407          1,665           767             975            1.78   17.68
  Sentistrength\_myspace   1,041          702             132             207            2.22   21.12
  Sentistrength\_rw        1,046          484             221             341            4.79   66.12
  debate                   3,238          730             1,249           1,259          1.86   14.86
  Sentistrength\_twitter   4,242          1,340           949             1,953          1.77   15.81
  English\_dailabor        3,771          739             488             2,536          1.54   14.32
  aisopos\_ntua            500            139             119             222            1.90   15.44
  sanders                  3,737          580             654             2,503          1.60   15.03
  tweet\_semevaltest       6,087          2,223           837             3,027          1.86   20.05

  : Labeled datasets details.[]{data-label="tab:labeled_dataset"}

Regarding the **baseline**, as 10SENT explores the output of 10 other individual methods, Majority Voting is a natural baseline[^2]. Voting is one of the simplest ways to combine several methods. By assuming that each individual method gives us a unique label as output for a sentence, the final result of Majority Voting is the label that the majority of the base classifiers returned as output for that sentence[^3].

The major advantages of this approach are its simplicity and extensibility, 