Attribute Sentiment Scoring with Online Text Reviews: Accounting for Language Structure and Missing Attributes

2021 ◽  
Author(s):  
Ishita Chakraborty ◽  
Minkyung Kim ◽  
K. Sudhir
Keyword(s):  
Language Structure ◽  
Missing Attributes

EXPRESS: Attribute Sentiment Scoring with Online Text Reviews: Accounting for Language Structure and Missing Attributes

2021 ◽  
pp. 002224372110525
Author(s):  
Ishita Chakraborty ◽  
Minkyung Kim ◽  
K. Sudhir
Keyword(s):  
Structural Model ◽  
Social Science Research ◽  
Science Research ◽  
Attribute Importance ◽  
Heterogeneous Model ◽  
Model Based ◽  
Language Structure ◽  
Status Seeking ◽  
Scoring Accuracy ◽  
Missing Attributes

The authors address two significant challenges in using online text reviews to obtain finegrained attribute level sentiment ratings. First, in contrast to methods that rely on word frequency, they develop a deep learning convolutional-LSTM hybrid model to account for language structure. The convolutional layer accounts for spatial structure (adjacent word groups or phrases) and LSTM accounts for sequential structure of language (sentiment distributed and modified across non-adjacent phrases). Second, they address the problem of missing attributes in text in constructing attribute sentiment scores—as reviewers write only about a subset of attributes and remain silent on others. They develop a model-based imputation strategy using a structural model of heterogeneous rating behavior. Using Yelp restaurant review data, they show superior attribute sentiment scoring accuracy with their model. They find three reviewer segments with different motivations: status seeking, altruism/want voice, and need to vent/praise. Reviewers write to inform and vent/praise, but not based on attribute importance. The heterogeneous model-based imputation performs better than other common imputations; and importantly leads to managerially significant corrections in restaurant attribute ratings. More broadly, our results suggest that social science research should pay more attention to reduce measurement error in variables constructed from text.

Socio-demographic influences on language structure and change: Not all learners are the same

2016 ◽  
Vol 39 ◽  
Author(s):  
Till Bergmann ◽  
Rick Dale ◽  
Gary Lupyan
Keyword(s):  
Adult Learners ◽  
Large Share ◽  
Demographic Differences ◽  
Language Structure

AbstractThe Now-or-Never bottleneck has important consequence for understanding why languages have the structures they do. However, not addressed by C&C is that the bottleneck may interact with who is doing the learning: While some languages are mostly learned by infants, others have a large share of adult learners. We argue that such socio-demographic differences extend and qualify C&C's thesis.

Language Structure and Language Aquisition

1982 ◽  
Vol 27 (1) ◽  
pp. 31-32
Author(s):  
Carlota S. Smith
Keyword(s):  
Language Structure ◽  
Language Aquisition

Zur Epistemologie gegenwärtiger Zeigeregime

2017 ◽  
Vol 8 (1) ◽  
pp. 41-60
Author(s):  
Karen Van den Berg
Keyword(s):  
User Interface ◽  
Symbolic System ◽  
Eine Analyse ◽  
Language Structure ◽  
The World

"Wie kommt es, dass sich der Flagship-Store eines Technikkonzerns präsentiert wie eine öffentliche Kunsthalle, während die Dependance des Louvre in Nord-Pas-de-Calais wirkt, als würde man eine iPad-Benutzeroberfläche betreten? Der Beitrag liefert eine Analyse des Louvre Lens und beleuchtet das Projekt in Hinblick auf seine verblüffenden ästhetischen Familienähnlichkeiten in Materialsprache, Struktur und Atmosphäre zu neueren Apple Stores. Dabei wird versucht, die kulturellen und mentalitätsgeschichtlichen Codes zu entziffern und zu plausibilisieren, dass sich hier eine Epistemologie entfaltet, die die Welt als simultan präsentes Symbolsystem begreift. How is it that the flagship store of a technology company presents itself as a public arthall, while the branch of the Louvre in Nord-Pas-de-Calais looks like the user interface of an iPad? The paper provides an analysis of the Louvre Lens and illuminates the project in terms of its stunning aesthetic similarities in material language, structure and atmosphere to recent Apple Stores. Furthermore, it attempts to decipher the cultural and mental-historical codes and argues that an epistemology is developing here which comprehends the world as a simultaneous symbolic system. "

scholarly journals Sensory Descriptor Analysis of Whisky Lexicons through the Use of Deep Learning

Foods ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1633
Author(s):  
Chreston Miller ◽  
Leah Hamilton ◽  
Jacob Lahne
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Descriptive Analysis ◽  
Food Products ◽  
Training Dataset ◽  
Test Accuracy ◽  
Language Structure ◽  
Deep Learning Model ◽  
Descriptor Analysis ◽  
Descriptive Language

This paper is concerned with extracting relevant terms from a text corpus on whisk(e)y. “Relevant” terms are usually contextually defined in their domain of use. Arguably, every domain has a specialized vocabulary used for describing things. For example, the field of Sensory Science, a sub-field of Food Science, investigates human responses to food products and differentiates “descriptive” terms for flavors from “ordinary”, non-descriptive language. Within the field, descriptors are generated through Descriptive Analysis, a method wherein a human panel of experts tastes multiple food products and defines descriptors. This process is both time-consuming and expensive. However, one could leverage existing data to identify and build a flavor language automatically. For example, there are thousands of professional and semi-professional reviews of whisk(e)y published on the internet, providing abundant descriptors interspersed with non-descriptive language. The aim, then, is to be able to automatically identify descriptive terms in unstructured reviews for later use in product flavor characterization. We created two systems to perform this task. The first is an interactive visual tool that can be used to tag examples of descriptive terms from thousands of whisky reviews. This creates a training dataset that we use to perform transfer learning using GloVe word embeddings and a Long Short-Term Memory deep learning model architecture. The result is a model that can accurately identify descriptors within a corpus of whisky review texts with a train/test accuracy of 99% and precision, recall, and F1-scores of 0.99. We tested for overfitting by comparing the training and validation loss for divergence. Our results show that the language structure for descriptive terms can be programmatically learned.

scholarly journals Subversion of Language Structure in Heterogeneous Speech Communities: the Work of Discourse and the Part of Contact

2008 ◽  
Vol 2 (1) ◽  
pp. 249-273 ◽  
Author(s):  
Katja Ploog
Keyword(s):  
Ivory Coast ◽  
Point Of View ◽  
Human Language ◽  
Speech Community ◽  
Language Structure ◽  
Speech Communities ◽  
Wide Range ◽  
Phonological Form ◽  
Bilingual Speaker ◽  
Actual Speech

AbstractChange is an ongoing process constitutive of human language to which will be refered by the term of dynamics. It will be worked out how mere interaction conditions the language dynamics and how the disposable structural resources will be coordinated in microsystems. Since from this point of view grammar exists as a process, it will be of interest to work out by what type of mechanisms a bilingual speaker elaborates his/her discourse. It will be discussed what can be called a (more) 'useful' construction and through what type of mechanisms the constructions get coordinated. We will argue that all discursive mechanisms are bound to satisfy the pragmatic demands of an actual speech production and that the most useful items are those which best satisfy these pragmatic demands.One of the most characteristic phenomena of the linguistic dynamics in Ivory Coast is the microsystem of LA: In a highly heterogeneous context of social interaction, LA is used in (the locally dominant) discursive traditions of French and Mande languages, undergoing a grammaticalization process separately in each of them and used - consequently - in various constructions. The wide range of its referential values, the very importance of the negotiation of discourse referents between speaker and hearer and its simple phonological form seem to predestine LA to get reappropriated and to become a 'favorite' form in the emergent speech community.

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