When Google Translate is better than Some Human Colleagues, those People are no longer Colleagues

We analyse posts on social media (Facebook, LinkedIn, and Twitter) as a means to understand how translators feel about machine translation (MT). A quantitative analysis of more than 13,000 tweets shows that negative perceptions outweigh positive ones by a ratio of 3:1 overall, and 5:1 in tweets relating MT to human translation. Our study indicates a disconnect between translation and research communities, and we outline three suggestions to bridge this gap: (i) identifying and reporting patterns rather than isolated errors, (ii) participating in evaluation campaigns, and (iii) engaging in cross-disciplinary discourse. Rather than pointing out each other's deficiencies, we call for computer scientists, translation scholars, and professional translators to advance translation technology by acting in concert.