بولدے درخت
کسے پنڈ وچ اک بہت ای سمجھ دار خاندان رہندا سی۔ اوس خاندان دے وڈے تاں اک پاسے بچے وی بہت سمجھ داری دیاں گلاں کردے سن، اوس خاندان دا اک بچہ جس دا ناں ’’ننھا‘‘ سی، ہر کسے نال بہت عقل مندی نال گل کروا تے لوک اوس دیاں گلاں سن کے حیران رہ جاندے تے اوس نال پیار کردے۔
اک دن اوہ پنڈ دے نیڑے جنگل وچ گیا۔ اوہنوں جنگل دی حالت ویکھ کے بہت دکھ ہویا کہ جنگل دے سارے رستیاں اتے گھاہ اُگیا ہویا اے۔ کئی درخت سک کے ڈگ پے نیں تے کئی سک دے جا رہے نیں۔ اوس نے تہیہ کیتا کہ اوہ جنگل دی صفائی ستھرائی ضرور کرے گا تے ایس لئی اوہ بادشاہ تک جاون لئی تیار ہو گیا۔
اک سویر اوہ بادشاہ دے دربار اندر پہنچ جاندا اے تے سب توں پہلاں اپنے پنڈ دا تعارف کروا ندا اے۔ اوس دسیا کہ میرا پنڈ بہت سوہنا اے تے پنڈ دے نال لگدا جنگل اوہناں ای گندا اے۔ مینوں ایہہ دسو تہاڈے دل وچ جنگل دی صفائی دا کدے خیال نئیں آیا۔ ایہہ گل سن کے بادشاہ سوچیں پے گیا تے سپاہیاں نوں بہت غصہ آیا۔ اوہناں ننھے نوں دربار وچوں کڈھن لئی پھڑیا۔ بادشاہ نے ایہہ ویکھ کے سپاہیاں نوں روکیا تے آکھیا بچے نوں بولن دیو۔ بادشاہ نے اوس کولوں اوہدا ناں پچھیا۔ اوس دسیا کہ میرا ناں ننھا ایں۔ میرا گھر ایسے پنڈ وچ اے تے میرے والد فوج وچ نوکری کر دے نیں۔ بادشاہ نے پچھیا توں کیہ چاہنا ایں؟ اوس جواب دتا کہ میری خواہش اے کہ میں جنگل دی صفائی کراں۔ تسی مینوں ایس کم دی اجازت دیو۔ کیوں جے ایہہ کم میں اکلا نئیں کر سکدا ایس لئی کجھ سپاہیاں نوں...
According to Qur’an, the difference of opinion among peoples of the world is natural and something that will always be there. However, in order to stop the difference from becoming a conflict, people should hold dialogue. The significance of dialogue in Islam is well understood by the fact that God chose to hold dialogue with angels concerning the creation of man. Furthermore, the Qur’an declares dialogue the greater jihad and arrangement of a successful dialogue is considered as a manifest victory In order to arrange a successful dialogue, Qur’an lays out a number of principles: 1- Dialogue should be held in such a nice way that it may lead the opponent to get a close friend. For this it is necessary to speak mildly and the dialogue must be based on wisdom and sincerity. 2- Dialogue should rest on the principle of mutual respect and should not contain any kind of abusive and taunting language. 3- Dialogue must not override the principle of justice and equality and must not be affected by the past experiences or personal grievances towards the opponent. 4- Dialogue should not address the issue of pulling everyone together, e.g. The opponent (for example a nation) should not be blamed for the evil deeds of few. 5- Dialogue should be held with an attitude that is characterized by patience and tolerance and efforts must be made to keep the vicious elements out from harming the process. 6- Both parties should openly acknowledge and recognize the mutually positive attributes. 7- Imposing one’s opinions upon the opponent must not be the objective of dialogue. 8- Both parties should, despite the inherent difference of opinion, pursue to find practical solutions by striving towards finding a common ground.
The Web 2.0 has dramatically changed people‟s communication style. It is a great move toward more community oriented, highly collaborative, interactive and responsive Web. Today we are not only using the Internet but we are part of this global network. Social media sites became the world‟s largest virtual community, where people express their views about products, events and services, anytime from anywhere. These views have great impact on community thinking and decisions. The most flourished feature of this era is the rising of blogging which provides resourceful and open way to anyone, anywhere. These data sources provide the rich basis for sentiment analysis. The statistics show that 80% of consumers have changed their decisions about purchase based on negative reviews found online. The study found that blogs are 63% more likely to influence purchase decisions than magazines. Evaluation of social media has powered interest in sentiment analysis. There exist two main approaches for extracting sentiment automatically, the lexicon-based approach and statistical or machine learning approach. The later approach demands a lot of training data to learn lexical items that express sentiment and its performance drops when the same classifiers is used in a different domain. The main focus of this work is to develop a lexicon-based framework for automatic classification of blogs and reviews with respect to their semantic orientation. This method consists of three major components: Sentiment analysis, Slang‟s detection and scoring, and Context-aware spelling corrector. Lexicon-based methods for sentiment analysis are robust, give good performance in cross-domain and can be easily boosted with additional source of knowledge. It performs well on blog posting, reviews and also a preferable classifier for handling contextual valence shifters. Irrespective of these merits no single lexicon can perform in an optimal way all the time. This method uses a dynamic, updateable and comprehensive lexicon based on existing opinion lexicons, dictionaries and other machine-readable resources to classify the user-generated contents into positive, negative and neutral polarity. vii Slangs and spelling correction are two vital elements for sentiment analysis because slang and misspelled word may affect the sentiment score. These two issues were handled using Web resources and Statistical language model. The proposed work was implemented, and evaluated with different datasets of reviews and blogs. The empirical results show that the proposed work outperforms the existing, related methods and achieves 90.3% accuracy on average. This method showed high accuracy in binary classification. All the three components of the proposed method performed well with different domains.