  TripAdvisor reviews and comparable data sources play an important role in
many tasks in Natural Language Processing (NLP), providing a data basis for the
identification and classification of subjective judgments, such as hotel or
restaurant reviews, into positive or negative polarities. This study explores
three important factors influencing variation in crowdsourced polarity
judgments, focusing on TripAdvisor reviews in Spanish. Three hypotheses are
tested: the role of Part Of Speech (POS), the impact of sentiment words such as
"tasty", and the influence of neutral words like "ok" on judgment variation.
The study's methodology employs one-word titles, demonstrating their efficacy
in studying polarity variation of words. Statistical tests on mean equality are
performed on word groups of our interest. The results of this study reveal that
adjectives in one-word titles tend to result in lower judgment variation
compared to other word types or POS. Sentiment words contribute to lower
judgment variation as well, emphasizing the significance of sentiment words in
research on polarity judgments, and neutral words are associated with higher
judgment variation as expected. However, these effects cannot be always
reproduced in longer titles, which suggests that longer titles do not represent
the best data source for testing the ambiguity of single words due to the
influence on word polarity by other words like negation in longer titles. This
empirical investigation contributes valuable insights into the factors
influencing polarity variation of words, providing a foundation for NLP
practitioners that aim to capture and predict polarity judgments in Spanish and
for researchers that aim to understand factors influencing judgment variation.
