{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T02:31:23Z","timestamp":1773801083217,"version":"3.50.1"},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAAI"],"abstract":"<jats:p>Existing Image-Text Sentiment Analysis (ITSA) methods may suffer from inconsistent intra-modal and inter-modal sentiment relationships. Therefore, we develop a method that balances before fusing to solve the issue of vision-language imbalance intra-modal and inter-modal sentiment relationships; that is, a Semi-Push-Pull Supervised Contrastive Learning (SPP-SCL) method is proposed. Specifically, the method is implemented using a novel two-step strategy, namely first using the proposed intra-modal supervised contrastive learning to pull the relationships between the intra-modal and then performing a well-designed conditional execution statement. If the statement result is false, our method will perform the second step, which is inter-modal supervised contrastive learning to push away the relationships between inter-modal. The two-step strategy will balance the intra-modal and inter-modal relationships to achieve the purpose of relationship consistency and finally perform cross-modal feature fusion for sentiment analysis and detection. Experimental studies on three public image-text sentiment and sarcasm detection datasets demonstrate that SPP-SCL significantly outperforms state-of-the-art methods by a large margin and is more discriminative in sentiment.<\/jats:p>","DOI":"10.1609\/aaai.v40i3.37200","type":"journal-article","created":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T22:58:14Z","timestamp":1773788294000},"page":"2173-2181","source":"Crossref","is-referenced-by-count":0,"title":["SPP-SCL: Semi-Push-Pull Supervised Contrastive Learning for Image-Text Sentiment Analysis and Beyond"],"prefix":"10.1609","volume":"40","author":[{"given":"Jiesheng","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengrong","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"9382","published-online":{"date-parts":[[2026,3,14]]},"container-title":["Proceedings of the AAAI Conference on Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/37200\/41162","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/37200\/41162","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T22:58:14Z","timestamp":1773788294000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/37200"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,14]]},"references-count":0,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2026,3,17]]}},"URL":"https:\/\/doi.org\/10.1609\/aaai.v40i3.37200","relation":{},"ISSN":["2374-3468","2159-5399"],"issn-type":[{"value":"2374-3468","type":"electronic"},{"value":"2159-5399","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3,14]]}}}