Task: Language Identification
Input (Spanish, English): # Summary  This paper presents an empirical study to identify a latent dimension of sentiment in word embeddings.  # Strengths   S1) Tackles a challenging problem of unsupervised sentiment analysis.   S2) Figure 2, in particular, is a nice visualisation.  # Weaknesses   W1) The experiments, in particular, are very thin. I would recommend also measuring F1 performance and expanding the number of techniques compared.   W2) The methodology description needs more organisation and elaboration. The ideas tested are itemised, but insufficiently justified.    W3) The results are quite weak in terms of the reported accuracy and depth of analysis. Perhaps this work needs more development, particularly with validating the central assumption that the Distributional Hypothesis implies that opposite words, although semantically similar, are separated well in the vector space?
Output (English): en