MORE THAN WORDS: A MULTI-DIMENSIONAL ANALYSIS OF ISLAMIC STATE LANGUAGE

ABSTRACT In this thesis I will provide an exploratory study applying Multi-Dimensional analysis to the realm of Islamic State language. Systematic, observable variables that constitute IS communications can be identified through a built model. The idea is to make more of the type of information that a human analyst relies on available in the automated pre-processing and parsing phases, the types of information that they are looking for is something that a system like Bag-of-Words is missing. The corpus studied was drawn from the Islamic State newsletter al-naba’. I collected five issues from January 2020 – February 2020. From those issues the editorial sections were focused on specifically. Two paragraphs were chosen from each editorial at random. Each paragraph was translated and coded for sixteen linguistic features, including the presence or absence of religious or political nouns and verbs. I ran a correlation matrix as well as a Factor Analysis and qualitatively analyzed each for the communicative functions. The statistical analysis revealed that overall, the Islamic State uses significantly more political speech than religious. However, in longer sentences, political and religious speech is more likely to occur. The qualitative analysis found that in longer sentences, religious and political speech are in service to each other. There is a political aim to the sentence punctuated with a religious admonition statement to reinforce the political goal. I hypothesize that MDA can determine, via a seeded exploration method, a distinct IS register among the newsletters. This thesis does not fully realize this goal; however, it does provide support for the concept by identifying patterns that may very well help to determine an IS register.Master of Art

Can humain association norm evaluate latent semantic analysis?

This paper presents the comparison of word association norm created by a psycholinguistic experiment to association lists generated by algorithms operating on text corpora. We compare lists generated by Church and Hanks algorithm and lists generated by LSA algorithm. An argument is presented on how those automatically generated lists reflect real semantic relations

Quality and productivity: A comparative analysis of human translation and post-editing with Malay learners of Arabic and English

Translation into and between foreign languages has become a common practice in the professional setting. However, this translation directionality has yet to be thoroughly explored, especially when post-editing is involved. The present study conducts experiments on the application of machine translation (MT) and translation memory (TM) in a translation classroom setting. A group of Malay speakers, who are non-native speakers of Arabic and English, used MemoQ 2014 to translate technical Arabic and English texts by post-editing raw MT and modified TM outputs containing several errors. The non-native trainee translators’ productivity was measured and the quality of the translation was assessed through error analysis approach based on the MeLLANGE error typology so that it could provide a comprehensive analysis of the types of errors commonly found in the non-native trainee translators’ translations. The error annotation also aims to provide guidelines for translators who work with the Arabic-English language pair and non-native translators. The present study revealed that the translation technologies helped improve the non-native translators’ speed and quality. The study also discovered that syntactic and lexical errors are the most problematic in the PE tasks. The trainee translators tend to overlook the errors that were caused by cross-linguistic influence, such as articles, gender, number and the conjunction “wa”. However, this could have been avoided if the participants revised their translations thoroughly because most of the errors are minor. The study also revealed that the non-native trainee translators could be as productive as the professional native translators because they managed to reach the average daily productivity for professional translators, which is at least 5,000 words per day

Quality and productivity: A comparative analysis of human translation and post-editing with Malay learners of Arabic and English

Translation into and between foreign languages has become a common practice in the professional setting. However, this translation directionality has yet to be thoroughly explored, especially when post-editing is involved. The present study conducts experiments on the application of machine translation (MT) and translation memory (TM) in a translation classroom setting. A group of Malay speakers, who are non-native speakers of Arabic and English, used MemoQ 2014 to translate technical Arabic and English texts by post-editing raw MT and modified TM outputs containing several errors. The non-native trainee translators’ productivity was measured and the quality of the translation was assessed through error analysis approach based on the MeLLANGE error typology so that it could provide a comprehensive analysis of the types of errors commonly found in the non-native trainee translators’ translations. The error annotation also aims to provide guidelines for translators who work with the Arabic-English language pair and non-native translators. The present study revealed that the translation technologies helped improve the non-native translators’ speed and quality. The study also discovered that syntactic and lexical errors are the most problematic in the PE tasks. The trainee translators tend to overlook the errors that were caused by cross-linguistic influence, such as articles, gender, number and the conjunction “wa”. However, this could have been avoided if the participants revised their translations thoroughly because most of the errors are minor. The study also revealed that the non-native trainee translators could be as productive as the professional native translators because they managed to reach the average daily productivity for professional translators, which is at least 5,000 words per day

How to even the score: an investigation into how native and Arab non-native teachers of English rate essays containing short and long sentences.

In the field of education, test scores are meant to provide an indication of test-takers’ knowledge or abilities. The validity of tests must be rigorously investigated to ensure that the scores obtained are meaningful and fair. Owing to the subjective nature of the scoring process, rater variation is a major threat to the validity of performance-based language testing (i.e., speaking and writing). This investigation explores the influence of two main effects on writing test scores using an analytic rating scale. The first main effect is that of raters’ first language (native and non-native). The second is the average length of sentences (essays with short sentences and essays with long sentences). The interaction between the main effects will also be analyzed. Sixty teachers of English as a second or foreign language (30 natives and 30 non-natives) working in Kuwait, used a 9-point analytic rating scale with four criteria to rate 24 essays with contrasting average sentence length (12 essays with short sentences on average and 12 with long sentences). Multi-Facet Rasch Measurement (using FACETS program, version 3.71.4) showed that: (1) the overall scores awarded by raters differed significantly in severity; (2) there were a number of significant bias interactions between raters’ first language and the essays' average sentence length; (3) the native raters generally overestimated the essays with short sentences by awarding higher scores than expected, and underestimated the essays with long sentences by awarding lower scores than expected. The non-natives displayed the reverse pattern. This was shown on all four criteria of the analytic rating scale. Furthermore, there was a significant interaction between raters and criteria, especially the criterion 'Grammatical range and accuracy'. Two sets of interviews were subsequently carried out. The first set had many limitations and its findings were not deemed adequate. The second set of interviews showed that raters were not influenced by sentence length per se, but awarded scores that were higher/lower than expected mainly due to the content and ideas, paragraphing, and vocabulary. This focus is most likely a result of the very problematic writing assessment scoring rubric of the Ministry of Education-Kuwait. The limitations and implications of this investigation are then discussed