跨目标立场检测研究综述

doi:10.3778/j.issn.1002-8331.2406-0268

摘要/Abstract

摘要： 跨目标立场检测利用源目标知识对新目标进行检测，减少了对新目标标注数据的需求，相较于传统的立场检测，能更好地适应快速发展的网络文化。目前关于立场检测研究综述成果众多，但跨目标立场检测研究仍缺少系统的总结与分析。在回顾近年来的跨目标立场检测领域相关研究的基础上，介绍了跨目标立场检测的基本概念，并从知识转移的角度对跨目标立场检测的研究方法进行了归纳总结；探讨了所有选定研究中用于跨目标立场检测的数据集的特点和局限性。最后，对该任务未来的发展趋势和挑战进行了展望。

关键词: 跨目标立场检测, 知识迁移, 外部知识, 立场检测

Abstract: Cross-target stance detection reduces the need for annotated data on new targets by using knowledge from source targets, making it more adaptable to the rapidly evolving online culture compared to traditional stance detection. At present, there are numerous research reviews on stance detection, but there is still a lack of systematic summary and analysis of cross-target stance detection. This paper reviews recent researches in the field of cross-target stance detection, introduces its fundamental concepts, and summarizes research methods from a knowledge transfer perspective. It discusses the characteristics and limitations of datasets used in selected studies. Finally, the future trends and challenges in this task are prospected.

Key words: cross-target stance detection, knowledge transfer, external knowledge, stance detection

任科兰, 张明书, 魏彬, 闫法成, 姜文. 跨目标立场检测研究综述[J]. 计算机工程与应用, 2025, 61(3): 21-33.

REN Kelan, ZHANG Mingshu, WEI Bin, YAN Facheng, JIANG Wen. Cross-Target Stance Detection: Review of Research[J]. Computer Engineering and Applications, 2025, 61(3): 21-33.

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