Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE)
This paper presents the findings of the preliminary analysis conducted on the Malaysian Corpus of Financial English (MaCFE). MaCFE is a specialised corpus consisting of written documents compiled from banks in Malaysia and the corpus is currently housing approximately 4.3 million word tokens. The ai...
| id |
Sadjirin R.; Aziz R.A.; Baharum N.D.; Nordin N.M.; Ismail M.R. |
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Sadjirin R.; Aziz R.A.; Baharum N.D.; Nordin N.M.; Ismail M.R. 2-s2.0-85092289385 Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE) 2020 3L: Language, Linguistics, Literature 26 2 10.17576/3L-2020-2602-14 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092289385&doi=10.17576%2f3L-2020-2602-14&partnerID=40&md5=5e9a4c78582b5d652d49c99855f7bd02 This paper presents the findings of the preliminary analysis conducted on the Malaysian Corpus of Financial English (MaCFE). MaCFE is a specialised corpus consisting of written documents compiled from banks in Malaysia and the corpus is currently housing approximately 4.3 million word tokens. The aim of the analysis was to evaluate the suitability of the texts chosen to represent the financial domain. The preliminary analysis involved generating the word list and lists of co-occurrences from MaCFE. RapidMiner Studio Educational 7.5.001 and an in-house Java programming solution was utilised to perform the analysis. The word list and lists of 50 most frequent two-word and three-word co-occurrences generated from the analysis reveal that the text compilation is representative of the financial domain in Malaysia. The study concludes by discussing the pedagogical implications of the findings. © 2020 Penerbit Universiti Kebangsaan Malaysia. All rights reserved. Penerbit Universiti Kebangsaan Malaysia 1285157 English Article All Open Access; Green Open Access |
| author |
2-s2.0-85092289385 |
| spellingShingle |
2-s2.0-85092289385 Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE) |
| author_facet |
2-s2.0-85092289385 |
| author_sort |
2-s2.0-85092289385 |
| title |
Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE) |
| title_short |
Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE) |
| title_full |
Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE) |
| title_fullStr |
Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE) |
| title_full_unstemmed |
Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE) |
| title_sort |
Preliminary Analysis of Malaysian Corpus of Financial English (MaCFE) |
| publishDate |
2020 |
| container_title |
3L: Language, Linguistics, Literature |
| container_volume |
26 |
| container_issue |
2 |
| doi_str_mv |
10.17576/3L-2020-2602-14 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092289385&doi=10.17576%2f3L-2020-2602-14&partnerID=40&md5=5e9a4c78582b5d652d49c99855f7bd02 |
| description |
This paper presents the findings of the preliminary analysis conducted on the Malaysian Corpus of Financial English (MaCFE). MaCFE is a specialised corpus consisting of written documents compiled from banks in Malaysia and the corpus is currently housing approximately 4.3 million word tokens. The aim of the analysis was to evaluate the suitability of the texts chosen to represent the financial domain. The preliminary analysis involved generating the word list and lists of co-occurrences from MaCFE. RapidMiner Studio Educational 7.5.001 and an in-house Java programming solution was utilised to perform the analysis. The word list and lists of 50 most frequent two-word and three-word co-occurrences generated from the analysis reveal that the text compilation is representative of the financial domain in Malaysia. The study concludes by discussing the pedagogical implications of the findings. © 2020 Penerbit Universiti Kebangsaan Malaysia. All rights reserved. |
| publisher |
Penerbit Universiti Kebangsaan Malaysia |
| issn |
1285157 |
| language |
English |
| format |
Article |
| accesstype |
All Open Access; Green Open Access |
| record_format |
scopus |
| collection |
Scopus |
| _version_ |
1828987873525760000 |