감성분석 목적의 한국어 평가 표현 연구 = A Study on Korean Appraisal Expressions for Sentiment Analysis|RISS 상세보기

다국어 초록 (Multilingual Abstract)

This study investigates how appraisals of target objects are linguistically realized in Korean product reviews under the goal of sentiment analysis. From the Functionalist linguistics perspective, language exists as a tool for communication, and speakers may choose particular lexis, grammatical structures, or broader patterns to convey their intentions. In other words, meaning emerges from “language in use,” placing greater emphasis on semantic and functional aspects rather than formal ones.
This study begins with the question: which expressions do speakers employ to reveal their own cognitive attitudes toward a target? Speakers may directly encode appraisals or judgments—using descriptors such as “good,” “bad,” or “beautiful”—but they also often utilize fact-stative expressions (e.g., “there are many flowers”) to convey an evaluation of a target’s aesthetic state indirectly. Notably, when such fact-stative expressions occur in contexts that communicate experiences of tourist sites, they can be interpreted as appraisals. This observation suggests that whether a factual description is construed as an appraisal depends on shared knowledge and contextual prerequisites among discourse participants.
Indeed, delineating precisely which linguistic expressions in discourse qualify as evaluations of a target is a highly demanding undertaking. J. Martin’s systemic-functional Appraisal Theory further exemplifies this challenge, as it continually uncovers the intricate and arduous nature of mapping the correlation between linguistic expressions and evaluative functions. In this way, the correlation between a given linguistic expression and its appraisal in discourse must take into account a variety of conditions—such as the type of appraisal target, the language community’s expectations of that target, the contextual factors surrounding the appraisal, and the relationships among interlocutors. However, because these factors are highly variable and complex, systematically defining and analyzing them is exceedingly difficult.
However, under the goal of sentiment analysis, it is feasible to identify the linguistic characteristics of speakers’ direct and indirect appraisals of a target. Because sentiment analysis focuses on publics’ positive and negative evaluations of items, the scope of appraisal targets can be narrowed to those entities or issues that attract public attention. In particular, when the discourse under investigation consists of product reviews, shared knowledge among interlocutors is confined to a specific product, and any omitted sentence elements can often be recovered easily from the product-review context. Moreover, since sentiment analysis centers on “positive–negative evaluation,” the difficulty of determining which expressions qualify as appraisals is somewhat alleviated. In other words, sentiment-analysis research conducted within the contextual constraints of product-review discourse—where both the appraisal target and context are relatively circumscribed—is well suited to exploring the linguistic realization of appraisal in discourse.
Meanwhile, much of the existing work in sentiment analysis has concentrated on individual words, constructing lexicons of positive and negative terms. In many dataset-building procedures, the text is first morphologically analyzed and POS-tagged, after which verbs and adverbs are extracted and assigned polarity labels. However, in actual language use, speakers do not restrict their appraisals to single words—word-focused methods centered on verbs and adverbs therefore have inherent limitations. Moreover, such lexicon-centric approaches often fail to account for instances where a potentially positive term’s evaluative force is neutralized or altered by specific grammatical constructions. Consequently, it is essential to move beyond word-level techniques and to analyze both lexical and grammatical expressions that realize appraisal in discourse, investigating their full range of semantic characteristics.
However widespread generative language models (LLMs) have become, the need for meticulously constructed sentiment‐analysis datasets remains high when accuracy and practical applicability are taken into account. Because appraisals are inherently context-dependent—even when defined simply as positive or negative evaluations—relying solely on general-domain LLMs limits one’s ability to perform fine-grained, domain- and context-specific sentiment analysis.
Accordingly, this study presents a comprehensive inventory of lexical and grammatical expressions that convey positive and negative sentiment, together with an analysis of their semantic and functional characteristics. The resulting catalog can serve as a set of seed words and constructions for researchers and practitioners across both academic and industrial contexts. More broadly, our findings offer a valuable starting point for understanding the linguistic features through which speakers express appraisal in discourse.
This study defines appraisal as the act of judging some aspect of an existing target as positive or negative. We broaden our scope beyond predicates and adverbs to include all parts of speech—including nouns—and extend our analysis to phrases and clauses.

The objectives of the present study are twofold:
(1) To identify which semantic properties of lexical items in product‐review discourse signal appraisal.
(2) To determine how grammatical meanings in product‐review discourse express or modulate appraisal.

In Chapter 2, we first survey both domestic and international research on sentiment and emotion analysis, alongside lexical classification studies conducted in Korean linguistics and language informatics. This review reveals that investigations into sentiment and emotion analysis have been pursued continuously across multiple arenas—from individual and corporate projects to national initiatives. However, dataset construction for sentiment analysis remains largely domain-specific. Accordingly, there is a pressing need to conduct cross-domain analyses that distinguish between (a) expressions that consistently convey positive or negative evaluations regardless of domain and (b) expressions whose evaluative force is confined to particular domains. Although the importance of such a distinction has been emphasized repeatedly, few studies have empirically attempted to extract truly domain-independent evaluative expressions through multi-domain analysis. Furthermore, certain classification categories—such as “price” or “design”—may function as universal sentiment dimensions across domains, underscoring the necessity of rigorous, empirical research in this area.
Secondly, it is somewhat regrettable that many sentiment‐analysis studies stop at the stage of listing lexical items without providing semantic justification for why those expressions convey positive or negative appraisal. If we understand the underlying semantic motivations, we can more effectively extend the inventory to include semantically similar expressions, thereby constructing sentiment lexicons with greater efficiency. Moreover, by examining how grammatical constructions themselves encode or modulate evaluative meaning, we can further enhance the accuracy of sentiment‐analysis systems.
Thirdly, although recent research has advanced toward fine‐grained, attribute‐based sentiment analysis, many studies still do not thoroughly address the problem of attribute extraction. As Kim Hansaem(2022) observes, distinguishing between entities and their evaluative attributes in annotated corpora is a challenging undertaking that demands dedicated investigation. By tackling this distinction head‐on, we can better support the development of high‐precision sentiment‐analysis resources.
Drawing on Korean lexical‐classification studies, we identified several shared criteria for distinguishing among parts of speech. In verb‐classification research—whether focused on case‐frame patterns or semantic properties—scholars commonly differentiate between eventivity and stativeity, as well as the animacy of the subject and whether the verb describes the subject’s psychological experience. In noun‐classification work, the prevailing distinctions concern whether a noun denotes a concrete entity (human or object) versus an abstract concept, and whether it expresses relational meaning with other lexical items. On this basis, our study adopts [eventivity], [stativeity], and the presence or absence of psychological‐state description as key semantic features for categorizing lexical items. Furthermore, in line with ontological and thesaurus‐based knowledge‐base practices, we abstract away from traditional part-of-speech boundaries, classifying expressions purely by their conceptual and semantic properties. We then examine how these semantically motivated categories relate to the realization of appraisal in product‐review discourse.
In Chapter 3, this study describes the research methodology. We constructed an 82,289-words, multi-domain corpus for sentiment analysis by extending the National Institute of Korean Language’s Attribute-Based Sentiment Analysis Corpus 2021 with additional product-review data. Four domains—beauty products (small-sized goods), home appliances (large-sized goods), lodging establishments (place-based services), and films (content products)—were each normalized to approximately 20,000 words to ensure balanced representation. To maximize the density of appraisal expressions, non-evaluative sentences from the primarily blog-style NIKL corpus were filtered out. In the beauty-product and film domains, roughly 70 percent of the original NIKL data were retained and supplemented with randomly sampled Naver beauty-product reviews from 2023 and Naver movie reviews from January through June 2024. For the home-appliances domain, we randomly sampled Naver product reviews from 2019, and for the lodging-establishment domain, we collected randomly sampled TripAdvisor reviews from 2023. This rigorously curated, multi-domain corpus enables a systematic exploration of appraisal expressions across varied product contexts while preserving both comparability and domain-specific richness.
I define the core terminology of this study. I distinguish sentiment expressions from appraisal expressions as follows. Sentiment expressions are those linguistic items that, by themselves, overtly convey a positive or negative evaluation of a target. In contrast, appraisal expressions form a broader category: they comprise any lexical or grammatical expression that, when accompanied by specific morphological or syntactic markers (e.g., attribute modifiers, evaluative particles), can function as a sentiment expression. Put differently, because our framework is grounded in attribute-based sentiment analysis, we treat sentiment expressions as the concatenation of an attribute expression and an appraisal expression—only in their combination does a full evaluative meaning emerge.
Also, this study also delineates the distinction between entities and attributes. Although entities ordinarily refer to a product’s components and attributes to its properties, this binary proves difficult to uphold in practice. In attribute-based sentiment analysis, attributes take precedence: they are the specific aspects or elements of a target that speakers judge positively or negatively. Consequently, the scope of an attribute varies with the analyst’s evaluative objectives and is formalized via the sentiment-analysis taxonomy. For the present study, we therefore define attributes as the concrete targets or elements that bear positive or negative evaluative polarity within attribute-based sentiment analysis.
I outline a seven-stage analysis procedure:
(1) Preprocessing: segmented the corpus into sentences—each assigned a unique index—and imported them into Excel to align with my clause-level analytical unit.
(2) Framework Development: established an attribute-based sentiment-analysis schema, defining the criteria for identifying appraisal expressions and tagging attributes.
(3) Polarity Annotation: applied this schema to assign positive or negative polarity to each evaluative instance.
(4) Expression & Attribute Tagging
(5) Distinguished into Attribute-Implicit and Attribute-Explicit expressions

I introduced two novel appraisal categories:
- Attribute-Implicit Expressions (속성내포형): Surface forms that do not overtly mark the attribute but whose semantics imply it (e.g., moisturizing).
- Attribute-Explicit Expressions (속성명시형): Forms that lexically specify the attribute being evaluated (e.g., rich in hydration, good moisturizing effect).

Although steps 2–4 were conducted interactively to ensure alignment between my schema and the data, this structured pipeline enabled a rigorous, reproducible analysis of appraisal expressions in product-review discourse.
I term linguistic expressions denoting attributes—such as 수분감 (moisture sensation) and 보습력 (moisturizing power)—as attribute expressions. To qualify as an attribute expression, I require three conditions to be met:
(1) It must constitute a separable linguistic unit at least at the phrase level.
(2) It must represent a specific positive or negative aspect of the product.
(3) The expression alone must not suffice to determine a positive, negative, or neutral evaluation.
Next, I conducted a correlation analysis between the semantic properties of lexical and grammatical expressions and their evaluative force. The central question was: “On what basis can a sentiment expression be interpreted as conveying positive or negative appraisal?” For example, the positive appraisal of expressions like “상품 좋다” (“the product is good”) and “디자인 예쁘다” (“the design is pretty”) rests on the fact that 좋다 and 예쁘다 carry positive lexical meanings. In contrast, the positive appraisal of “사용할 만하다” is licensed by the grammatical construction ‘-(으)ㄹ 만하다’ (pronounced [-(eu)l manhada]), which grammatically encodes the positive sense of “to be worth doing.” Thus, an expression’s evaluative polarity in discourse may derive either from its inherent lexical semantics (as in the first case) or from the semantic contribution of a grammatical marker (as in the second). In this study, I analyzed whether each extracted sentiment expression’s evaluative basis is attributable to its lexical-semantic properties or to the semantics of its grammatical construction.
When the basis for sentiment expressions resides in lexical items, I first conducted semantic‐feature grouping, followed by an analysis of the correlation between semantic features and appraisal. Semantic‐feature grouping began with initial lexical clusters derived from existing semantic‐attribute classification studies; I then iteratively refined these clusters by typologically analyzing the list of sentiment expressions extracted from the corpus. In Chapter 5, I present the correlation‐analysis results by dividing the clusters into three types.
By contrast, for the correlation analysis between grammatical expressions and appraisal realization, I did not perform semantic‐feature grouping. Instead, I directly analyzed the correlation across all grammatical constructions observed in the data. This approach reflects the tendency—already noted in this study—for lexical items, rather than grammatical forms, to bear the primary evaluative load. For the grammatical analysis, I relied on the Kim et al (2005) dictionary of grammatical constructions.
In Chapter 4, I present the results of sentiment analysis across the four selected domains. This chapter details the factors considered in constructing the sentiment classification schema, the attribute analysis, and the domain‐specific inventory of attribute‐implicit and attribute‐explicit sentiment expressions. Its purpose is not merely to report the evaluative profiles of beauty products, home appliances, lodging establishments, and films, but to reveal how reviewers perceive the contextual framing of each product type and linguistically realize their appraisals.
Overall, the material‐goods domains (beauty products and home appliances) and the place‐service domain (lodging establishments) share common evaluative dimensions—such as price, design (aesthetic qualities), tactile experience, and service quality. In contrast, the film domain, as a content product, exhibits minimal overlap with these categories, aside from “fame” and “target audience.” Moreover, the film reviews demonstrate that a complete understanding of cinematic evaluation often requires integrating emotion analysis alongside sentiment analysis. This chapter’s findings offer practical guidance for analysts on the domain‐specific considerations essential to accurately capturing appraisal expressions in product‐review discourse.
In Chapter 4, I move beyond a mere report of sentiment‐analysis results for the four domains. Instead, I introduce and justify the novel distinction between attribute-implicit and attribute-explicit expressions—thereby addressing long-neglected questions of attribute definition, delimitation, and extraction. As attribute-based sentiment analysis gains traction, the critical issue becomes how analysts should conceptualize attributes, construct classification schemas, and handle product-review corpora in practice.
- Attribute-implicit expressions can be directly mapped to domain-specific appraisal categories within each sentiment‐classification framework.
- Attribute-explicit expressions, as composites of an attribute expression and an appraisal expression, suggest a two-stage lexicon approach: (1) build separate attribute and appraisal dictionaries, then (2) establish domain-appropriate mapping rules between them to efficiently manage and extend both resources.
Moreover, by applying synonym-expansion techniques to both dictionaries, one can enrich coverage with expressions not attested in the original corpus. These strategies collectively provide a scalable, systematic method for capturing evaluative language in diverse product‐review contexts.
In Chapter 5, I investigate how the semantic characteristics of both lexical and grammatical expressions correlate with positive and negative appraisal in product‐review discourse. First, I identify two classes of lexical items that consistently function as evaluative markers: affective expressions (e.g., terms denoting pleasure or displeasure) and sensory expressions (e.g., descriptors of texture or scent). Affective expressions further subdivide into domain-independent items that convey approval or disapproval regardless of context and domain-dependent items whose evaluative force varies by product category. Sensory expressions—since they reflect the reviewer’s direct perceptual experience—almost invariably participate in appraisal across all four domains.
Next, I turn to lexical expressions whose evaluative status depends on contextual or syntactic conditions. Appearance descriptors such as aesthetic or cleanliness terms generally carry appraisal, whereas descriptions of shape or passive constructions only do so when paired with specific attribute expressions or within particular domains. Property-descriptive terms tend to map onto concrete product attributes and exemplify the attribute-implicit category introduced earlier. Emotion terms likewise display varying behavior: core feel-good words (joy, fun, awe, relief, confidence) and core feel-bad words (resentment, disgust, aversion, embarrassment) appear universally as evaluative, while a second set of emotions (trust, hope, gratitude, regret, worry) requires morpho-syntactic support to function as appraisal. In the film domain, additional emotion words (empathy, anger, sadness, fear, surprise, bittersweetness) bridge sentiment and emotion analysis. Perceptual-cognitive expressions—aside from a few like “understand”—also need co-occurrence with attribute markers or contextual cues to convey evaluation, and eventivity expressions that imply repeat purchase or ongoing use consistently signal positive appraisal.
Finally, I examine non-lexical items—comparatives, degree modifiers, and material descriptors—that themselves lack inherent polarity but serve as functional operators completing the appraisal when combined with attribute expressions. Together, these findings clarify the precise conditions under which various linguistic features realize positive and negative evaluations in product‐review discourse, offering a nuanced account of how speakers linguistically encode appraisal across diverse domains.
In Chapter 6, I investigate the correlation between grammatical constructions and evaluative polarity in product‐review discourse. I first identify a set of grammatical markers that consistently convey positive or negative appraisal: ‘-(으)ㄹ 만하다’, ‘-어/아 보세요’, ‘-(으)ㄹ 수 있다’, ‘-(으)면 되다’, ‘-어/아도 되다’, and ‘-기는 하다’. Each of these constructions either inherently encodes a positive meaning or is employed in evaluative contexts so reliably that it functions as a grammatical appraisal expression.
Beyond these unambiguous cases, I show that certain mood and modality markers—those expressing unmet conditions ([condition]), desire ([wish]), or volition ([will])—serve evaluative functions only when combined with particular lexical items. For example, ‘-(으)면’ in the conditional yields a positive appraisal when its protasis is negated and its apodosis contains a regret‐laden term; when followed by simple approval verbs like ‘좋다’ or ‘괜찮다’, it signals weak positive or neutral appraisal. The necessity marker ‘-어/아야’, when paired with positively valenced descriptions, conveys neutral-to-weakly negative evaluation by implying obligation. The wish construction ‘-(으)면 좋겠다’, combined with positive appraisal verbs, paradoxically delivers a negative evaluation by highlighting the absence of the desired state; its variant used in film‐review contexts (e.g., “I wish there were a sequel”) functions as a positive appraisal. Volitional forms (e.g., ‘-겠-’, ‘-어/아야겠다’, ‘-(을) 것이다’, ‘-(으)ㄹ게요’) become evaluative only when they express intention to repurchase or continue use.
I also explore how case particles contribute to evaluation. The comparative particle ‘만큼’, when used with expectation nouns or price attributes, carries evaluative weight, while the limiting particle ‘만’, when followed by action‐oriented verbs or positive appraisal adjectives, distributes positive appraisal to the specified attribute and negative appraisal elsewhere. The copular particle ‘이다’ assists in realizing appraisal by asserting the presence of a valued attribute (e.g., “has a sea view”). Lastly, I document several context‐dependent appraisal constructions—such as the imperative ‘-(으)세요’, the retrospective ‘-(으)ㄹ 텐데’ and ‘-(으)ㄹ걸’, the obligation marker ‘-어/아야 하다’, and aspectual ‘-어/아 버리다’—noting that some (e.g., causatives ‘-게 하다’, ‘-게 만들다’) are evaluative only in the film domain or when combined with perceptual‐cognitive terms, and that certain markers (e.g., ‘-(으)ㄹ 때’) can neutralize a preceding appraisal. Through this comprehensive analysis, Chapter 6 delineates the precise grammatical conditions under which Korean evaluative meanings emerge in product‐review discourse.
In Chapters 5 and 6, I examine how distinct semantic features shape positive and negative polarity judgments from the perspectives of lexis and grammar, respectively. In Chapter 5, I demonstrate that simple affective terms and sensory descriptors invariably signal evaluative polarity, making them prime candidates for inclusion in appraisal lexicons. Aesthetic- and cleanliness-related appearance descriptors, together with certain property descriptors and emotion terms whose polarity is unambiguous, likewise function consistently as evaluative markers. By contrast, the remaining appearance and property descriptors, as well as many emotion, perceptual-cognitive, and eventivity expressions, require specific contextual or attribute-expression conditions before their polarity can be resolved; this insight informs domain-sensitive sentiment‐analysis strategies. Notably, my finding that comparative, degree-modifier, and material expressions serve primarily as functional operators—while the attribute expressions themselves determine evaluative value—highlights the existence of different classes of attribute expressions: some merely denote product features or components, while others, by virtue of being mentioned, presuppose the presence of an attribute and thus influence polarity judgment. Distinguishing between these attribute classes will be an important focus for future research.
Chapter 6 of this study is significant in that it ventures into a largely unexplored territory: the relationship between grammatical constructions and positive–negative appraisal judgments. While most sentiment-analysis research has focused on lexical items and produced extensive word lists, I demonstrate that certain purely grammatical markers—though devoid of inherent evaluative meaning—become integral components of sentiment expressions when combined with other elements. These constructions not only contribute to the assignment of polarity but, in some cases, actually trigger polarity shifts or neutralization. This finding underscores the need for future sentiment-analysis frameworks and datasets to extend beyond the lexicon and systematically incorporate grammatical phenomena.
Nonetheless, a limitation of Chapter 6 is that it stops at cataloguing the grammatical appraisal expressions that influence polarity decisions. Although it is plausible that these constructions’ modal nuances play a crucial role in their evaluative function, the present study does not undertake a deep examination of their modality features. Subsequent research that probes these morphosyntactic subtleties would not only enrich our understanding of how speakers linguistically realize appraisal but also enhance the precision and sophistication of sentiment-analysis methodologies.
When humans evaluate a target, they may employ direct lexical or expressive means—such as affective or emotion terms that reveal the speaker’s judgment or psychological state—but they also frequently use ostensibly factual descriptions (e.g., appearance or property descriptors) to convey positive or negative appraisal. Furthermore, under certain contextual conditions, expressions of obligation or volition can likewise function as evaluative markers. While lexical semantic features exert the primary influence on the realization of evaluative polarity, grammatical semantics also contribute to the expression or neutralization of such judgments; hence, both lexical and grammatical meanings must be considered in appraisal analysis. Many expressions—such as fact‐descriptive language, eventivity terms, and volitional or deontic constructions—are interpretable as evaluative only by virtue of interlocutors’ expectations and the shared knowledge of the discourse community. The sentiment analysis presented here ultimately concerns the study of how speakers’ evaluations are linguistically manifested, underscoring that any research engaging with the semantic dimension of Korean text must be grounded in rigorous linguistic inquiry. Because sentiment analysis interrogates both the latent meanings of expressions and the speaker’s intent, careful interpretation of surface‐level language forms is inseparable from linguistic theory. By integrating linguistics’ conceptual frameworks and empirical findings with the goals of sentiment analysis, this study provides a model for the definition, development, and application of analytical methods required to bridge theory and practice.

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국문 초록 (Abstract)

기능주의 관점에서 언어는 의사소통의 도구로서 존재하며 ’사용으로서의 언어(language in use)’일 때 언어의 실제 의미를 알 수 있다고 본다. 그렇다면 화자는 어떤 표현을 사용하여 대상에 대한 자신의 인지적 태도를 드러내는가? 본 연구는 이 문제를 탐구하기 위해 시작되었다. 사실상 담화에서 어느 언어 표현까지가 대상에 대한 평가를 나타내는가의 문제를 규명하는 일은 평가 대상 및 맥락 요소, 화청자 간의 공유 지식이 매우 다변적이고 복합적으로 얽혀 있다는 점에서 매우 어려운 과업이다. 그러나 상품평 담화 대상의 감성분석(sentiment analysis)은 ‘대상에 대한 대중의 긍부정 평가’이기 때문에 평가 대상과 맥락 요소가 어느 정도 한정되므로 담화에서 평가하기의 언어적 실현을 탐구하는 것이 가능해진다.
본 연구는 상품평 담화의 감성분석이라는 목적 아래 한국어 담화에서 대상에 대한 평가가 어떤 언어적 특질을 보이며 실현되는가에 대해 탐구한 연구이다. 연구의 대상은 용언, 부사, 명사를 포함한 모든 품사와 구, 절 단위까지 포괄하였으며 연구의 목적은 상품평 담화에서 어휘와 문법의 어떤 의미가 긍부정 평가를 나타내거나 혹은 조정할 수 있는지를 밝히는 데 두었다.
2장에서는 이론적 논의를 주제별로 감성분석과 감정분석 연구 분야 중 데이터 구축과 관련한 국내외 성과, 국어학과 언어 정보학의 어휘 분류 연구에 대하여 살펴보았다. 3장에서는 본 연구의 감성분석용 말뭉치의 구성과 분석 방법에 대해 기술하였다. 분석용 말뭉치는 국립국어원의 '속성 기반 감성분석 말뭉치 2021'를 기본 토대로 구성하였으며 부족분에 대해서는 네이버 및 트립어드바이저 상품평을 추가 수집하였다. 말뭉치는 총 82,289 어절로서 미용제품, 가전제품, 숙박업소, 영화 이렇게 총 4개의 도메인으로 구성되었다. 분석 방법은 먼저 4개 도메인 대상으로 감성 분류 체계를 수립하고 감성분석을 수행한 후 개체와 속성을 구분하였다. 그다음에 ‘속성내포형’과 ‘속성명시형’의 개념을 정립 후 감성표현을 이 두 유형별로 제시하였다. 속성내포형은 속성이 언어적으로 드러나지 않고 그 의미가 어휘에 포함된 형태이며 속성명시형은 속성이 언어적으로 명시된 형태를 가리킨다. 이 두 분류를 기초로 하여 4장에서 각 도메인별 속성 분석 결과와 속성별 감성분석 결과를 제시하였다.
4장을 통해 총 4개 도메인의 감성 분류 체계의 구성 예시와 각 도메인별 속성 표현, 감성표현 목록, 속성과 감성의 구분 문제에 대해 고찰해 볼 수 있었다. 미용·가전·숙박업소 도메인에서는 가격, 디자인, 사용감, 서비스 등 공통 평가 항목이 존재했으나, 영화는 유명도와 이용대상 외에는 겹치는 평가 항목이 거의 없었고 감정분석까지 함께 수행해야 평가가 완전해짐을 확인했다. 또한 속성 분석을 통해 동일한 속성 표현이 함께 결합하는 평가 표현에 따라 지시 속성이 달라질 수 있다는 점 등을 추가로 확인할 수 있었다.
5장에서는 어휘 표현을 의미 특성별로 유형화하여 이 의미 특성이 상품평 담화에서의 긍부정 평가 판별에 어떤 상관성이 있는지를 분석하였다. 상품평 담화에서 항상 긍부정 평가를 나타낼 수 있는 어휘 평가 표현은 호감도 표현, 감각 표현이 있었다. 맥락 조건 혹은 형태·통사적 조건이 주어질 때만 제한적으로 긍부정 평가를 보이는 어휘 평가 표현으로는 외형 묘사 표현, 성질 묘사 표현, 감정 표현, 지각인지 표현, 행위성 표현이 있었다. 마지막으로 비교 표현, 정도성 표현, 소재 표현은 감성표현을 구성하는 기능어로서의 역할을 담당하고 있었다.
6장에서는 문법 표현의 의미가 상품평 담화에서 긍부정 평가 실현에 어떤 영향을 미치는지를 분석하였다. 상품평 담화에서 항상 긍부정 평가를 보이는 문법 평가 표현은 긍부정 의미를 내포하거나 담화 내 쓰임이 긍부정 판단의 묘사인 경우였는데 ‘-(으)ㄹ 만하다’, ‘-어/아 보세요’, 가능의 ‘-(으)ㄹ 수 있다’, ‘-(으)면 되다’, ‘-어/아도 되다’. ‘-기는 하다’가 해당하였다. 둘째로 담화에서 특정한 어휘 평가 표현과 결합할 때 제한적으로 긍부정 평가를 보이는 문법 표현들로는 [조건], [소망], [의지]와 같이 미경험 전제의 문법 표현, 조사 ‘만큼, 만, 이다’, [명령]. [후회], 사동, [의무], ‘-어/아 버리다’, ‘-어/아 보이다’, [비유] 문법 표현이 있었다. 그리고 [목적], [시간] 문법 표현은 단순 만족도 표현과 같이 전형적으로 긍부정 평가를 드러내는 어휘 평가 표현과 결합 시 오히려 어휘의 긍부정 평가를 상실시키는 효과를 냈다.
본고의 연구 결과는 향후 다방면에서 감성분석용 지식 구축 시 필수적으로 고려해야 하는 감성 분류 체계, 속성 표현, 감성표현, 속성과 감성의 구분 문제에 대해 실제적으로 도움을 줄 수 있을 것이다. 또한 한국어 상품평 담화에서 긍부정 평가 판단에 영향을 미치는 어휘와 문법의 의미 특성을 규명하고 그 목록과 고려 요인을 제공하였다는 점에서 언어학 연구 성과를 실제 감성분석에 접목한 충분한 가치를 지닌다.

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기능주의 관점에서 언어는 의사소통의 도구로서 존재하며 ’사용으로서의 언어(language in use)’일 때 언어의 실제 의미를 알 수 있다고 본다. 그렇다면 화자는 어떤 표현을 사용하여 대상에 ...

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