{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/public-wisdom-matters-discourse-aware","title":"Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social-Text Classification","arxiv_id":"2209.13017","date":"2022-09-15","proceeding":null,"authors":["Karish Grover","S. M. Phaneendra Angara","Md. Shad Akhtar","Tanmoy Chakraborty"],"abstract":"Social media has become the fulcrum of all forms of communication. Classifying social texts such as fake news, rumour, sarcasm, etc. has gained significant attention. The surface-level signals expressed by a social-text itself may not be adequate for such tasks; therefore, recent methods attempted to incorporate other intrinsic signals such as user behavior and the underlying graph structure. Oftentimes, the `public wisdom' expressed through the comments/replies to a social-text acts as a surrogate of crowd-sourced view and may provide us with complementary signals. State-of-the-art methods on social-text classification tend to ignore such a rich hierarchical signal. Here, we propose Hyphen, a discourse-aware hyperbolic spectral co-attention network. Hyphen is a fusion of hyperbolic graph representation learning with a novel Fourier co-attention mechanism in an attempt to generalise the social-text classification tasks by incorporating public discourse. We parse public discourse as an Abstract Meaning Representation (AMR) graph and use the powerful hyperbolic geometric representation to model graphs with hierarchical structure. Finally, we equip it with a novel Fourier co-attention mechanism to capture the correlation between the source post and public discourse. Extensive experiments on four different social-text classification tasks, namely detecting fake news, hate speech, rumour, and sarcasm, show that Hyphen generalises well, and achieves state-of-the-art results on ten benchmark datasets. We also employ a sentence-level fact-checked and annotated dataset to evaluate how Hyphen is capable of producing explanations as analogous evidence to the final prediction.","url_abs":"https://arxiv.org/abs/2209.13017v2","url_pdf":"https://arxiv.org/pdf/2209.13017v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"public-wisdom-matters-discourse-aware","repo_url":"https://github.com/LCS2-IIITD/Hyphen","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"abstract-meaning-representation","task_name":"Abstract Meaning Representation"},{"task_slug":"fake-news-detection","task_name":"Fake News Detection"},{"task_slug":"graph-representation-learning","task_name":"Graph Representation Learning"},{"task_slug":"hate-speech-detection","task_name":"Hate Speech Detection"},{"task_slug":"rumour-detection","task_name":"Rumour Detection"},{"task_slug":"sarcasm-detection","task_name":"Sarcasm Detection"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"text-classification-1","task_name":"text-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2209.13017","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.13017"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/LCS2-IIITD/Hyphen","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":6},"by_repo_kind":{"official":{"samples":6,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"eef7c8d5cf600055","entry":"E2Lorentz","repo":"LCS2-IIITD/Hyphen","repo_kind":"official","path":"hypPostEnc.py","file_url":"https://github.com/LCS2-IIITD/Hyphen/blob/HEAD/hypPostEnc.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"eef7c8d5cf600055"}},{"code_sha256_prefix":"6bf9c25d96d8780e","entry":"L2Klein","repo":"LCS2-IIITD/Hyphen","repo_kind":"official","path":"hypPostEnc.py","file_url":"https://github.com/LCS2-IIITD/Hyphen/blob/HEAD/hypPostEnc.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"6bf9c25d96d8780e"}},{"code_sha256_prefix":"dde0071f9cb5ca8c","entry":"P2Lorentz","repo":"LCS2-IIITD/Hyphen","repo_kind":"official","path":"hypPostEnc.py","file_url":"https://github.com/LCS2-IIITD/Hyphen/blob/HEAD/hypPostEnc.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"dde0071f9cb5ca8c"}},{"code_sha256_prefix":"b901e87c0c073e6b","entry":"get_data","repo":"LCS2-IIITD/Hyphen","repo_kind":"official","path":"preprocess.py","file_url":"https://github.com/LCS2-IIITD/Hyphen/blob/HEAD/preprocess.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b901e87c0c073e6b"}},{"code_sha256_prefix":"69003c42a5f83853","entry":"to_dict","repo":"LCS2-IIITD/Hyphen","repo_kind":"official","path":"amr/amr_dgl.py","file_url":"https://github.com/LCS2-IIITD/Hyphen/blob/HEAD/amr/amr_dgl.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"69003c42a5f83853"}},{"code_sha256_prefix":"3f0f74c3c3a14bb5","entry":"var2word","repo":"LCS2-IIITD/Hyphen","repo_kind":"official","path":"amr/amr_dgl.py","file_url":"https://github.com/LCS2-IIITD/Hyphen/blob/HEAD/amr/amr_dgl.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"3f0f74c3c3a14bb5"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}