The Indonesian and english argument structure

1999 ◽  
Vol 22 (2) ◽  
pp. 85-102 ◽  
Author(s):  
Safnil Arsyad
Keyword(s):  
Text Analysis ◽  
Argument Structure ◽  
Native Speakers ◽  
Analysis Model ◽  
Analysis Techniques ◽  
Argumentative Text ◽  
Text Features ◽  
Organisational Structures ◽  
Rhetorical Structures ◽  
Argumentative Texts

This study examined and compared the rhetorical structure of argumentative texts written by three groups of university students: 1° twenty Indonesian texts written by Indonesian native speakers (I.I); 2° ten English texts written by Indonesian native speakers (I.E); and 3° ten English texts written by English native speakers (A.E). Following the argumentative text analysis model developed by Tirkkonen-Condit (1984 and 1986) and Connor (1990), the data were analysed using top-down and bottom-up analysis techniques at macro organisational text level. The results indicated that the text organisational structures of argumentative texts in English and in Indonesian were different in respect of the frequency of occurrence of sections—introduction, evaluation and conclusion— and of the sub-sections of refutation, sub-claim, and induction within the problem section. Cultural differences between English and Indone-sian may have played a crucial role in the text rhetorical differences. Also, the I.E. text features are more similar to those of the A.E. texts than to those of the I.I. texts. The study indicates that the Indonesian students need to study the conventions of rhetorical structures and text features of English argumentative texts in order to be able to write good argumentative texts in English.

Intercultural Discourse Patterns in Writing Argumentative Texts

2008 ◽  
Vol 156 ◽  
pp. 153-168
Author(s):  
Bruria Margolin ◽  
Hanna Ezer
Keyword(s):  
Student Teachers ◽  
Native Speakers ◽  
First Year ◽  
Writing Quality ◽  
Discourse Patterns ◽  
Jewish Students ◽  
Arab Students ◽  
Text Features ◽  
Argumentative Texts

This study examines the quality of the writing of Jewish (L1) and Arab (L2) first-year student teachers at Hebrew-speaking colleges. The study seeks to understand the quality of argumentative writing of the student teachers at the beginning of their studies and to expose the discourse patterns that emerge from those argumentative texts. A code book serving as a coding analysis device was developed in order to reveal the following rhetorical text features: content, structure, syntax and style. Each global feature contained a number of specific measures. The findings indicate that the writing quality of first-year L1 students is significantly higher than that of first-year L2 students on all the specific writing measures examined. The texts of the Arab students were less coherent and lacked rhetorical structure and accepted grammatical forms, whereas those of the Jewish students were more coherent and self-explanatory. The study concludes that when Arab students write in Hebrew as a second language, the linguistic and rhetorical conventions of Arabic interfere with their Hebrew writing. The results demonstrate significant and interesting differences between Jewish native speakers (L1 students) and Arab non-native speakers (L2 students). While the texts of L1 students tend to display 'explicit coherence,' those of L2 students show 'implicit coherence.'

Intercultural Discourse Patterns in Writing Argumentative Texts

2008 ◽  
Vol 156 ◽  
pp. 153-168
Author(s):  
Bruria Margolin ◽  
Hanna Ezer
Keyword(s):  
Student Teachers ◽  
Native Speakers ◽  
First Year ◽  
Writing Quality ◽  
Discourse Patterns ◽  
Jewish Students ◽  
Arab Students ◽  
Text Features ◽  
Argumentative Texts

Abstract This study examines the quality of the writing of Jewish (L1) and Arab (L2) first-year student teachers at Hebrew-speaking colleges. The study seeks to understand the quality of argumentative writing of the student teachers at the beginning of their studies and to expose the discourse patterns that emerge from those argumentative texts. A code book serving as a coding analysis device was developed in order to reveal the following rhetorical text features: content, structure, syntax and style. Each global feature contained a number of specific measures. The findings indicate that the writing quality of first-year L1 students is significantly higher than that of first-year L2 students on all the specific writing measures examined. The texts of the Arab students were less coherent and lacked rhetorical structure and accepted grammatical forms, whereas those of the Jewish students were more coherent and self-explanatory. The study concludes that when Arab students write in Hebrew as a second language, the linguistic and rhetorical conventions of Arabic interfere with their Hebrew writing. The results demonstrate significant and interesting differences between Jewish native speakers (L1 students) and Arab non-native speakers (L2 students). While the texts of L1 students tend to display 'explicit coherence,' those of L2 students show 'implicit coherence.'

scholarly journals Depression-level assessment from multi-lingual conversational speech data using acoustic and text features

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Cenk Demiroglu ◽  
Aslı Beşirli ◽  
Yasin Ozkanca ◽  
Selime Çelik
Keyword(s):  
Text Analysis ◽  
Training Data ◽  
Conversational Speech ◽  
Acoustic Feature ◽  
The World ◽  
Significant Burden ◽  
Depression Assessment ◽  
Depression Level ◽  
Text Features ◽  
Multiple Languages

AbstractDepression is a widespread mental health problem around the world with a significant burden on economies. Its early diagnosis and treatment are critical to reduce the costs and even save lives. One key aspect to achieve that goal is to use technology and monitor depression remotely and relatively inexpensively using automated agents. There has been numerous efforts to automatically assess depression levels using audiovisual features as well as text-analysis of conversational speech transcriptions. However, difficulty in data collection and the limited amounts of data available for research present challenges that are hampering the success of the algorithms. One of the two novel contributions in this paper is to exploit databases from multiple languages for acoustic feature selection. Since a large number of features can be extracted from speech, given the small amounts of training data available, effective data selection is critical for success. Our proposed multi-lingual method was effective at selecting better features than the baseline algorithms, which significantly improved the depression assessment accuracy. The second contribution of the paper is to extract text-based features for depression assessment and use a novel algorithm to fuse the text- and speech-based classifiers which further boosted the performance.

Why is this happened? Passive morphology and unaccusativity

1997 ◽  
Vol 13 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Patricia Balcom
Keyword(s):  
Argument Structure ◽  
Native Speakers ◽  
Control Group ◽  
Past Participle ◽  
Production Task ◽  
Syntactic Rule ◽  
English Writing ◽  
The Past ◽  
Linguistic Representations ◽  
Unaccusative Verbs

Zobl discussed inappropriate passive morphology (‘be’ and the past participle) in the English writing of L2 learners, linking its occurrence to the class of unaccusative verbs and proposing that learners subsume unaccusatives under the syntactic rule for passive formation. The research reported here supports and amplifies Zobl' proposal, based on a grammaticality judgement task and a controlled production task containing verbs from a variety of subclasses of unaccusatives. The tasks were administered to Chinese L1 learners of English and a control group of English native speakers. Results show that subjects both used and judged as grammatical inappropriate passive morphology with all verbs falling under the rubric of unaccusativity. The article concludes with linguistic representations which maintain Zobl’s insights but are consistent with current theories of argument structure.

Brand Positioning and Segmentation of Sneakers through Multi-Dimensional Customer Experience Analysis

2021 ◽  
Vol 13 (2) ◽  
pp. 335-345
Author(s):  
R. Senthilkumar ◽  
B. RubanRaja ◽  
Monisha
Keyword(s):  
Text Analysis ◽  
Customer Experience ◽  
Structured Data ◽  
Multivariate Techniques ◽  
Brand Positioning ◽  
Customer Reviews ◽  
Perceptual Mapping ◽  
Analysis Techniques ◽  
Hidden Patterns ◽  
And Cluster Analysis

A huge corpus of valuable information on customer experience is available as unstructured form in customer reviews on e-commerce websites. Multivariate data analysis techniques are effective in uncovering hidden patterns and segments in structured data. A major challenge is to convert the unstructured data into a structured form for applying multivariate techniques. In this article, we have provided a text analysis based approach coupled with multivariate techniques to uncover the sentiment of various features associated with different brands and to determine the brand positions and segments through perceptual mapping and cluster analysis.

scholarly journals Analisis Keserasian Belanja Daerah Kabupaten Garut

2018 ◽  
Vol 10 (2) ◽  
pp. 87-95
Author(s):  
Abdal Abdal ◽  
Herabudin Herabudin ◽  
Siti Saodah
Keyword(s):  
Data Analysis ◽  
Qualitative Approach ◽  
Fiscal Year ◽  
Capital Expenditures ◽  
Analysis Model ◽  
Analysis Techniques ◽  
Three Stages ◽  
Operating Expenditures ◽  
Descriptive Method ◽  
Year 2013

The problem in this study relates to the level of compatibility of operating expenditures, capital expenditures as well as direct and indirect expenditure in the Budget Realization Report (LRA) Garut district fiscal year 2013-2017. The aim of this study was to determine the level of compatibility of operating expenditures, capital expenditures, as well as direct and indirect expenditure on Budget Realization Report (BRR) Garut regency Fiscal Year 2013-2017. The method used in this research is descriptive method with qualitative approach. Data collection techniques in this study is the observation, documentation, interviews and triangulation. Data analysis techniques in this study is an analysis model of Miles and Huberman which consists of three stages: 1) Reduction of data, 2) data, and 3) conclusion / verification. The result is the expenditures to Garut regency 2013-2017 fiscal year quite well.

scholarly journals INDIGO DALAM NOVEL SUPERNOVA AKAR KARYA DEE LESTARI: KAJIAN PSIKOLOGI SASTRA

EDU-KATA ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. 141-148
Author(s):  
Erna Rakhmawati
Keyword(s):  
Data Analysis ◽  
Text Analysis ◽  
Textual Analysis ◽  
Literary Works ◽  
Analysis Techniques ◽  
Descriptive Research ◽  
Qualitative Descriptive ◽  
The Subject

The background of this research is many indigo events in the community and many indigo literary works. Indigo research in the  “Indigo dalam Novel Supernova Akar Karya Dee Lestari:Tinjauan Psikologi Sastra,” first aims to find the description of the indigo abilities experienced by the characters, secodly to find the causes of indigo experienced by characters, and thirdly to find out the type of indigo experienced by characters in the Supernova Akar. The research includes qualitative descriptive research on data analysis techniques using textual analysis or text analysis. The subject of this study is a character in the Supernova Akar. The result of research that is narated by Dee lestari source are; 1)levitasi, 2) procegnition, 30 psicometri, 4) teleportasi, and 5) clayvoyance. Indigo causes experienced by characters in the Supernova Akar are; 1) a gift from God, 2) from offspring, and from training. The type of indigo experienced by characters in the Supernova Akar are; humanis and artis.

A Study and Comparison of Sentiment Analysis Techniques Using Demonetization

2019 ◽  
pp. 1-14 ◽  
Author(s):  
Krishna Kumar Mohbey ◽  
Brijesh Bakariya ◽  
Vishakha Kalal
Keyword(s):  
Sentiment Analysis ◽  
Text Analysis ◽  
Analytical Approach ◽  
Document Type ◽  
Analysis Techniques

Sentiment analysis is an analytical approach that is used for text analysis. The aim of sentiment analysis is to determine the opinion and subjectivity of any opinion, review, or tweet. The aim of this chapter is to study and compare some of the techniques used to classify opinions using sentiment analysis. In this chapter, different techniques of sentiment analysis have been discussed with the case study of demonetization in India during 2016. Based on the sentiment analysis, people's opinion can be classified on different polarities such as positive, negative, or neutral. These techniques will be classified on different categories based on size of data, document type, and availability. In addition, this chapter also discusses various applications of sentiment analysis techniques in different domains.

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