{'fraction_non_alphanumeric': 0.022222222222222223, 'fraction_numerical': 0.0, 'mean_word_length': 5.693069306930693, '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}}
Construction of an Evaluation Corpus for Opinion Extraction

Opinion retrieval aims to tell if a document is positive, neutral or negative on a given topic. Opinion extraction further identifies the document’s supportive and the non-supportive evidence. This paper defines the annotation of opinionated material. The algorithm employs opinion holders, a topic’s conceptual words, sentiment words, opinion operators, and negation operators to recognize opinions. An opinion extraction system is developed and then reflects the major views of selected information sources. The text-based evidence extracted is ready for opinion summarization and opinionated question answering.