{'fraction_non_alphanumeric': 0.018198362147406732, 'fraction_numerical': 0.00272975432211101, 'mean_word_length': 4.945945945945946, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Native Sentiment Analysis Tools vs. Translation Services - Comparing GerVADER and VADER

VADER is a rule-based sentiment analysis tool for English texts with a social media focus. GerVADER is a German adaptation of VADER, which was developed following the steps of VADER’s development process. VADER showed high F1 scores especially for the social media domain, whereas the German adaptation achieved much lower results within the same domain, although on other test data. In this work we examine the question of whether these differences are language-specific. Therefore we apply an improved version of GerVADER to German texts and compare the results with the application of VADER to the same texts that are automatically translated into English. The benchmarking showed, that the translation combined with VADER achieves up to 5% higher F1 scores in all test cases, which can be explained by the translation tools automatic fixing of flawed sentences. However, native language tools can still be viable, since it saves time and costs and does not need another dependency to a third party service.