٭ اثر صہبائی، بام رفعت، لاہور ، اکادمی پنجاب ،۱۹۵۴ء
٭ اثر صہبائی، بحضورؐ سرور کائنات ، لاہور، انجمن حمایت اسلام، س۔ن
٭ اثر صہبائی، جام صہبائی، لاہور، دار اللتالیف ،۱۹۳۸ء
٭ اثر صہبائی، جام طہور، لاہور، تاج کمپنی لمیٹڈ، ۱۹۳۷ء
٭ اثر صہبائی، خمستان، لاہور، تاج کمپنی لمیٹڈ، ۱۹۳۷ء
٭ اثر صہبائی، ر وح صہبائی، لاہور، تاج کمپنی لمیٹڈ ،۱۹۳۷ء
٭ اثر صہبائی، راحت کدہ، لاہور، تاج کمپنی لمیٹڈ، ۱۹۴۲ء
٭ اثر صہبائی، محبت کے پھول ، لاہور ، نوائے وقت پرنٹرز،۱۹۶۳ء
٭ اثر صہبائی، نور و نکہت، کراچی، اردو اکیڈمی سندھ ، ۱۹۵۹ء
٭ اجمل نیازی، ڈاکٹر، فوق الکشمیر، لاہور ، سنگ میل پبلی کیشنز،۱۹۹۰
٭ احسان اﷲ ثاقب، ’’ شہر غزل‘‘ ، لاہور، معراج پرنٹرز،۲۰۰۶ء
٭ اخلاق اثر، ڈاکٹر، ( مرتب) ، اقبال نامے، بھوپال، طارق پبلی کیشنز ، ۱۹۸۱
٭ اسلم ملک، اقبال مفکر پاکستان، لاہور، اکبر امین پریس، ۱۹۹۷ء
٭ اسلم ملک، بچوں کا اقبال، لاہور، اکبر امین پریس، ۲۰۰۰ء
٭ اسلم ملک، علامہ اقبال بچپن اور جوانی، ایضاً، ۲۰۰۰ء
٭ اسلم ملک، مرتب بخدمت اقبال ، لاہور، اکبر امین پریس ،۲۰۰۰ء
٭ اسلم ملک، ’’ مطالعات اقبال‘‘ ، سیالکوٹ،اردو ادب اکیڈمی، ۱۹۶۹ء
٭ اشتیاق احمد(مرتب)، ’’ فیض احمد فیض کی شاعری‘‘ ،لاہور ، کتاب سرائے،۲۰۱۰ء
٭ اشفاق نیاز، ’’ تاریخ سیالکوٹ‘‘ ، سیالکوٹ، سیالکوٹ ایڈورٹائزرز،۲۰۰۹ء
٭ اصغر سودائی، ’’ چلن صبا کی طرح‘‘ ، لاہور، صدیقی...
This article maps the role of religion in the prevalence and promotion of honour killing in tribal areas of Pakistan. Through simple sampling method a sample size of 377 respondents, comprising of ‘Maliks’ were selected from the study universe. The collected data was interpreted and presented at uni-variate, bi-variate and multi-variate levels. Chi-square test statistics were used to draw association between dependent variable (honour killing) and independent variable (religion) both at bi-variate and multi-variate levels. The study found a significant relationship of honour killing with the importance of religion in people lives, alienation from the religious teachings, dominance of cultural values over religion, existence of honour killing in all religious sects (Shia and Sunni), and lack of factual religious knowledge about honour killing. Moreover, a non-significant relationship of honour killing was found with permission of honour killing in Islam, and religious clerics often speak about honour killing in religious sermons. Understanding of women and their rights in light of the teachings of Islam, religious clerics need to perform their true role, and killing in either shape needs to be propagated as against the religion were presented some of the policy recommendations in lights of the study results.
In computational linguistics, sentiment analysis facilitates classification of opinion as a positive or a negative class.In last decade, the area of sentiment analysis of English language is explored largely with different techniques those have improved the overall performance.Urdu is language of sixty-six million people and largely spoken in south-asian subcontinent. Also, it is national language of Pakistan which is world sixth most populous country according to United Nations Population Division. Sentiment analysis of Urdu language is important tool to understand the behavioural aspects, cultural values and social habits of the people living in this part of world. Opinion mining is also crucial for governments, policy makers, business owners and brand ambassadors to make their decisions in accordance to sentiment of the public.However, sentiment analysis of Urdu language is not well explored as that of English language. The Urdu sentiment analysis is performed with simple Bag-of-Word (BoW) method and machine learning (ML) techniques with limited set of features. The BoW method is not sufficient to handle complex opinions. Also, the accuracy of ML techniques, with legacy features, is not comparable to the sentiment classification task of other languages. For English language, the discourse information (sub-sentence level information) boosted the performance of both BoW method and ML techniques. A theory for Urdu sentiment analysis that extract and use the discourse information at sub sentence level and also suggest a computational model to achieve more accurate and better results than the simple bag of word approach. The proposed solution segmented the sentiment into two sub-opinions, extracted discourse information (discourse relation and polarity relation), proposed an extended BoW method (rule based method) and suggested a new small subset of features for ML techniques. The results significantly enhance (p < 0.001) the performance of recall, precision and accuracy by 37.25%, 8.46%, and 24.75% respectively. The current research targeted sentiment with two sub-opinions that remain excellent until the opinions are short messages like those on Twitter, in forum comments or as Facebook status posts. The proposed technique can be extended for sentiments with more than two sub-opinions such as blogs, reviews, and TV talk shows.