Výsledky vyhledávání - "Kim Schouten"

Dynamics and tipping point of issue attention in newspapers

Autor: Alette Eva Opperhuizen, Kim Schouten

Publikováno v: Quality and Quantity, 55(1), 19-37. Springer Netherlands

This study aims to provide a more sensitive understanding of the dynamics and tipping points of issue attention in news media by combining the strengths of quantitative and qualitative research. The topic of this 25-year longitudinal study is the vol

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb62c14499b442a72e0e351e3c64d014
https://doi.org/10.1007/s11135-020-00992-w

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How do media, political and regulatory agendas influence one another in high risk policy issues?

Autor: Erik-Hans Klijn, Kim Schouten, Alette Eva Opperhuizen

Publikováno v: Policy & Politics, 48(3), 461-483. Policy Press

This article shows how an emerging risk is covered by the media and how this interacts with political attention and policy implementation. Gas drilling has resulted in earthquakes in the Netherlands over the past 25 years. We show that an increase in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c9acab5610ca0421eb2106b12cd75c0
https://doi.org/10.1332/030557319x15734252420020

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Framing a Conflict! How Media Report on Earthquake Risks Caused by Gas Drilling

Autor: Erik-Hans Klijn, Alette Eva Opperhuizen, Kim Schouten

Publikováno v: Journalism Studies, 20(4), 714-734. Routledge

Using a new analytical tool, supervised machine learning (SML), a large number of newspaper articles is analysed to answer the question how newspapers frame the news of public risks, in this case of earthquakes caused by gas drilling in The Netherlan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae9e9bfa7d0a659730d9d5317bc94aa4
https://doi.org/10.1080/1461670x.2017.1418672

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Supervised and Unsupervised Aspect Category Detection for Sentiment Analysis With Co-Occurrence Data

Autor: Kim Schouten, Rommert Dekker, Flavius Frasincar, Onne van der Weijde

Publikováno v: IEEE Transactions on Cybernetics, 48(4), 1263-1275. IEEE

Using online consumer reviews as electronic word of mouth to assist purchase-decision making has become increasingly popular. The Web provides an extensive source of consumer reviews, but one can hardly read all reviews to obtain a fair evaluation of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a986e21eaac60fb3ba75afcb3bbeaf7
https://hdl.handle.net/1765/108656

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SOBA: Semi-automated Ontology Builder for Aspect-Based Sentiment Analysis

Autor: Flavius Frasincar, Kim Schouten, Lisa Zhuang

Publikováno v: Journal of Web Semantics, 60:100544. Elsevier

This research explores the possibility of improving knowledge-driven aspect-based sentiment analysis (ABSA) in terms of efficiency and effectiveness. This is done by implementing a Semi-automated Ontology Builder for Aspect-based sentiment analysis (

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c669a8914339db3b9b1a063327f4ff9c
https://pure.eur.nl/en/publications/bd3e4b77-33c3-405f-8163-030f3516b7cf

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SASOBUS: Semi-automatic Sentiment Domain Ontology Building Using Synsets

Autor: Kim Schouten, Flavius Frasincar, Lisa Zhuang, Ewelina Dera

Publikováno v: 17th Extended Semantic Web Conference (ESWC 2020), 105-120
STARTPAGE=105;ENDPAGE=120;TITLE=17th Extended Semantic Web Conference (ESWC 2020)
The Semantic Web ISBN: 9783030494605
ESWC

In this paper, a semi-automatic approach for building a sentiment domain ontology is proposed. Differently than other methods, this research makes use of synsets in term extraction, concept formation, and concept subsumption. Using several state-of-t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::934246dc7ce05d3aa8be7ac482afc3f4
https://pure.eur.nl/en/publications/3fe73ee8-5d5d-44ca-abc8-1e4955b173f7

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Exploring Lexico-Semantic Patterns for Aspect-Based Sentiment Analysis

Autor: Frederique Baas, Nikki van de Ven, Alexander Osinga, Olivier Bus, Kim Schouten, Steffie van Loenhout, Lisanne Vrolijk, Flavius Frasincar

Publikováno v: SAC
34th ACM/SIGAPP Symposium on Applied Computing (SAC ’19), 984-992
STARTPAGE=984;ENDPAGE=992;TITLE=34th ACM/SIGAPP Symposium on Applied Computing (SAC ’19)

Web 2.0 has caused a boom in user-generated content, which contains a lot of valuable information. Analysis of these natural language data requires advanced machine learning techniques. This research focuses on determining aspect-based sentiment in c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f245029e291c950f02a6c7bbf18a1f47
https://doi.org/10.1145/3297280.3297377

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Heracles: A Framework for Developing and Evaluating Text Mining Algorithms

Autor: Kim Schouten, Rommert Dekker, Flavius Frasincar, Mark Riezebos

Publikováno v: Expert Systems with Applications, 127, 68-84. Elsevier Ltd.

Many of today’s businesses are driven by data, and while traditionally only quantitative data is considered, the role of textual data in our digital world is rapidly increasing. Text mining allows to extract and aggregate numerical data from textua

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6ccff25756b0cef7b14bb52c47075ab
https://pure.eur.nl/en/publications/b9d872c0-2210-4d4a-9514-8b2e3ed9ff38

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Survey on Aspect-Level Sentiment Analysis

Autor: Kim Schouten, Flavius Frasincar

Publikováno v: IEEE Transactions on Knowledge and Data Engineering, 28(3), 813-830. IEEE Computer Society

The field of sentiment analysis, in which sentiment is gathered, analyzed, and aggregated from text, has seen a lot of attention in the last few years. The corresponding growth of the field has resulted in the emergence of various subareas, each addr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42ce76f6c9baa59f71e1fe62493ca6b0
https://pure.eur.nl/en/publications/f83ba7d2-edae-42ce-9fd3-88176bf2335e

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Ontology-Driven Sentiment Analysis of Product and Service Aspects

Autor: Kim Schouten, Flavius Frasincar

Publikováno v: 15th Extended Semantic Web Conference (ESWC 2018), 608-623
STARTPAGE=608;ENDPAGE=623;TITLE=15th Extended Semantic Web Conference (ESWC 2018)
The Semantic Web ISBN: 9783319934167
ESWC

With so much opinionated, but unstructured, data available on the Web, sentiment analysis has become popular with both companies and researchers. Aspect-based sentiment analysis goes one step further by relating the expressed sentiment in a text to t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06cb0b78694af99e660be94aa6889189
https://pure.eur.nl/en/publications/70f29d87-57fa-4029-bdea-67445ab99dc9

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