{"paper":{"title":"Identifying Structures in Social Conversations in NSCLC Patients through the Semi-Automatic extraction of Topical Taxonomies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.IR","authors_text":"Amir A. Delay, Fatemeh Seyedmendhi, Giancarlo Crocetti","submitted_at":"2016-02-12T19:56:49Z","abstract_excerpt":"The exploration of social conversations for addressing patient's needs is an important analytical task in which many scholarly publications are contributing to fill the knowledge gap in this area. The main difficulty remains the inability to turn such contributions into pragmatic processes the pharmaceutical industry can leverage in order to generate insight from social media data, which can be considered as one of the most challenging source of information available today due to its sheer volume and noise. This study is based on the work by Scott Spangler and Jeffrey Kreulen and applies it to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.04709","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}