Do you want to publish a course? Click here

The Social Criticism in Andalucia Context "Magamat"

النّقد الاجتماعي في المقامة الأندلسيّة

1512   1   58   0 ( 0 )
 Publication date 2015
  fields Arabic
and research's language is العربية
 Created by Shamra Editor




Ask ChatGPT about the research

Al-Andalucia Magamat book was not far away from the variety of life scenes intheir society.But,by their intelligent awareness they could select some of their problems and re-organise them in artistic picture,trying seriously to find suitions.they conceived by their deep sight how to react sensibly with their fact,when they wanted to depict a phenomenon.They used certain tools to depict the corruption describing the state,the complaint,the sarcasm,the humour and Al-Makdi type.This study aims to throw thelight on these tools which Al-Makdi writers and the Andalucians used to direct their critical arrows towards all that caused their psychological pressure.This study also depends on descriptionand analysis as a method to achieve this aim.

References used
ابراهيم، مصطفى عبد الرحمن، في النقد الأدبي القديم عند العرب، مكة للطباعة، 1998 م.
الإفريقي ، ابن منظور، لسان العرب، دار الفكر، ط1 , 1428.
ابن خاقان، قلائد العقيان و محاسن الأعيان ،حققه و علّق عليه: حسين خريوش، مكتبة المنار،ط 1, 1989م.
rate research

Read More

The speech act of complaining is used by humans to communicate a negative mismatch between reality and expectations as a reaction to an unfavorable situation. Linguistic theory of pragmatics categorizes complaints into various severity levels based o n the face-threat that the complainer is willing to undertake. This is particularly useful for understanding the intent of complainers and how humans develop suitable apology strategies. In this paper, we study the severity level of complaints for the first time in computational linguistics. To facilitate this, we enrich a publicly available data set of complaints with four severity categories and train different transformer-based networks combined with linguistic information achieving 55.7 macro F1. We also jointly model binary complaint classification and complaint severity in a multi-task setting achieving new state-of-the-art results on binary complaint detection reaching up to 88.2 macro F1. Finally, we present a qualitative analysis of the behavior of our models in predicting complaint severity levels.
The present study seeks to identify the nature of the relationship between social reality and consciousness from a perspective that we call interactive, and to examine their contribution to the social character of the other. In particular, consider ation of the relationship between reality and consciousness has often taken a unilateral character in the discussions about it, whether among sociologists in particular, or among the scholars in social sciences in general, where the focus was on the identification of the pre-existing of consciousness or the existence. In so far as the difference in responses has enriched sociology with opinions and theories to the extent that it has left a profound impact on the point of view of the assessment of what is the primary and what is marginal in the relationship between consciousness and social existence. Apart from these unilateral and sharp estimates, the present study attempts to clarify the relationship between social consciousness and social existence through what can be called the picture of reality in the minds of social actors as embodied by the reality of the relationship between values and reality because values constitute an important aspect of consciousness and, at the same time, directing people's relations and
Social media texts such as blog posts, comments, and tweets often contain offensive languages including racial hate speech comments, personal attacks, and sexual harassment. Detecting inappropriate use of language is, therefore, of utmost importance for the safety of the users as well as for suppressing hateful conduct and aggression. Existing approaches to this problem are mostly available for resource-rich languages such as English and German. In this paper, we characterize the offensive language in Nepali, a low-resource language, highlighting the challenges that need to be addressed for processing Nepali social media text. We also present experiments for detecting offensive language using supervised machine learning. Besides contributing the first baseline approaches of detecting offensive language in Nepali, we also release human annotated data sets to encourage future research on this crucial topic.
Sarcasm is a linguistic expression often used to communicate the opposite of what is said, usually something that is very unpleasant with an intention to insult or ridicule. Inherent ambiguity in sarcastic expressions makes sarcasm detection very dif ficult. In this work, we focus on detecting sarcasm in textual conversations, written in English, from various social networking platforms and online media. To this end, we develop an interpretable deep learning model using multi-head self-attention and gated recurrent units. We show the effectiveness and interpretability of our approach by achieving state-of-the-art results on datasets from social networking platforms, online discussion forums, and political dialogues.
The study has been done during the period 2014/2015 by field study and by using data from government instituations of the area and data collected by questionair the study has concluded some economic indicators of the area development : the percapit a income was 293 sp/aday = 1.63 $/aday . So it was below the global provety line (2 us $ aday) but higher than the global extreme poverty line.and this means that the percaptia income permonth was 8790 sp , which is below the percaptia income permonth (14.068sp) and that the government jobs contributed by 83% of the overall area income while the contribution of the agriculture was only 11.4% and of water business was 5.6 % . Also, the study also showed that borrowing has played a significant role in improving the quality of life , and that there was iequlity in the distribution of income as shown by Lorenz curve and thevalue of Gini coefficient of income distribution 0.46 .
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا