Image Retrieval for Arguments Using Stance-Aware Query Expansion

Abstract

Many forms of argumentation employ images as persuasive means, but research in argument mining has been focused on verbal argumentation so far. This paper shows how to integrate images into argument mining research, specifically into argument retrieval. By exploiting the sophisticated image representations of keyword-based image search, we propose to use semantic query expansion for both the pro and the con stance to retrieve "argumentative images" for the respective stance. Our results indicate that even simple expansions provide a strong baseline, reaching a precision@10 of 0.49 for images being (1) on-topic, (2) argumentative, and (3) on-stance. An in-depth analysis reveals a high topic dependence of the retrieval performance and shows the need to further investigate on images providing contextual information.

Annotation for computational argumentation analysis: Issues and perspectives

“…3 Argumentation mining has so far focused on text -but there are examples of other modalities being investigated such as images (Kiesel et al, 2021) or speech (Lippi & Torroni, 2016). 4 In this and several other areas of NLP, machine learning (especially so-called deep learning, now often referred to as "AI" in public discourse) has completely superseded rule-based methods, so that we do not currently find argumentation analysis systems like that described by Cohen (1987).…”

“… 3 3 Argumentation mining has so far focused on text – but there are examples of other modalities being investigated such as images (Kiesel et al., 2021) or speech (Lippi & Torroni, 2016). …”