ECO v1: Towards Event-Centric Opinion Mining (2022)

Abstract: Events are considered as the fundamental building blocks of the world. Mining event-centric opinions can benefit decision making, people communication, and social good. Unfortunately, there is little literature addressing event-centric opinion mining, although which significantly diverges from the well-studied entity-centric opinion mining in connotation, structure, and expression. In this paper, we propose and formulate the task of event-centric opinion mining based on event-argument structure and expression categorizing theory. We also benchmark this task by constructing a pioneer corpus and designing a two-step benchmark framework. Experiment results show that event-centric opinion mining is feasible and challenging, and the proposed task, dataset, and baselines are beneficial for future studies.

## introduction events are the fundamental building blocks of the world @xcite . we express, share and propagate our opinions about events with personal understandings, emotions and attitudes in our daily life. people can better understand, communicate and interact with each other by mining, sharing and exchanging event-centric opinions. and being exposed to event-centric opinions from different angles can debias people's own emotions and attitudes about social issues @xcite . therefore, mining event-centric opinions have huge social and personal impacts. unfortunately, there is little literature addressing event-centric opinion mining, and most of current opinion mining studies focus on entity-centric opinions, which significantly diverge from the concerning event-centric ones. first, entity-centric opinions mostly focus on sentimental polarity of given an event, people can express their judgements, beliefs, attitudes and suggestions. the opinions oriented to an event may not directly target at itself, but can target at its related subevents or entities. the holder @xcite , meanwhile event-centric opinions care more about the content such as nonsentimental judgments, predictions or suggestions. second, due to the rich interactions between events, entities, and people, event-centric opinions have a complicated structure. given an event, people can express their opinions about the event itself, as well as its subevents, related events, and the involved entities. third, the expressions of eventcentric opinions are unique. the targets of eventcentric opinions are frequently implicitly referred to, which often don't appear in the opinion expressions. moreover, event-centric opinions are usually widely spread in long news and passages, which are mixed up with facts and non-opinion information. by contrast, entity-centric opinions mainly appear in short and focused reviews or comments individually. the above connotation, structure, and document event-centric opinions opinion target extraction event-oriented opinion extraction judgement snippet o 1 ={ s 2 ,s 3 } belief snippet o 2 = s 6 suggestion snippet o 3 = s 7 [a1] samsung wins appeal in patent dispute with apple [a2]: patent dispute [a3] : apple opinion o 1 a1 opinion o 2 ## event-centric opinion mining this section first defines the connotation and targets of event-centric opinions. then we will formulate the task of event-centric opinion mining. ## benchmarking event-centric opinion mining this section benchmarks event-centric opinion mining with a two-step framework. two feasible solutions are proposed for each step, and therefore lead to 4 different benchmark architectures. ## related work previous opinion mining (om) researches focus on entity-centric opinions @xcite , which mainly categorizes the holder's sentiments towards entities and their attributes at document-level @xcite @xcite @xcite , sentence-level @xcite @xcite @xcite and aspect-level @xcite @xcite @xcite @xcite @xcite @xcite . there are also some researches working on event-related opinions @xcite @xcite @xcite . generally speaking, these studies commonly regard event as a special type of entity, neglecting the unique characteristics of event-centric opinions. however, events are very different from entities, and therefore eventcentric opinions have different connotations and targets which have not been exploited yet. for the evaluation resource of om, most of current studies are based on the semeval challenges datasets @xcite @xcite and its extension @xcite @xcite , which consist of entity-centric customer reviews about target entities from 7 domains. to the best of our knowledge, the constructed eco bank is the first publicly available event-centric opinion mining benchmark from news domain, which definitely can benefit future research in this direction. ## conclusions and future work in this paper, we propose and formulate eventcentric opinion mining, a new task that aims to mine a broader range of opinions oriented to specific events from documents. an event-centric opinion bank corpus is constructed and a two-step framework is proposed. experiments demonstrate the challenges and advantages of mining eventcentric opinions. the focus of this paper is the introduction of the new task and datasets. the proposed four baseline systems are relatively simple and leave much room for further improvements. in future work, we will try to build end-to-end models that directly extract opinion triples in an end-to-end fashion and enrich the current opinion structure.