اسلام زندہ ہوتا ہے ہر کربلا کے بعد
نحمدہ ونصلی علی رسولہ الکریم امّا بعد فاعوذ بااللہ من الشیطن الرجیم
بسم اللہ الرحمن الرحیم
صدر بزم و معزز اساتذہ کرام اور میرے ہم مکتب ساتھیو!
آج مجھے جس موضوع پرلب کشائی کا موقع فراہم کیا گیا ہے ،وہ کچھ یوں ہے:
’’اسلام زندہ ہوتا ہے ہر کربلا کے بعد ‘‘
معزز سامعین!
تاریخ حق و باطل میں خیر و شر کے لاکھوں معرکے ہوئے، ہزاروں شہادتیں ہوئیں۔ اسلام کا اوّلین دور لاتعداد شہادتوں سے لبریز ہے مگر جو شہرت حضرت امام حسین ؓ کو حاصل ہوئی وہ کسی اور کو نصیب نہ ہو سکی۔ آج تک کسی شہادت کو اس قدر شہرت، قبول عام اور ہمہ تذکرہ نصیب نہ ہو سکا جتنا امام حسین ؓ کو ہوا ہے۔ تقریباً ساڑھے تیرہ سو سال گزرنے کے باوجودبھی شہادت امام حسین ؓکا ذکر زندہ و تابندہ ہے۔ حسینیت ہر طبقے میں حق اور یزید یت ہر طبقے میں فتنہ و فساد کی علامت بن گئی ہے۔
حاضرین محفل!
جب یزید تخت نشین ہوا تو اس نے اپنے اقتدار کی راہ میں حائل ہر رکاوٹ کو بڑی بے دردی اورسختی سے دور کرنا شروع کر دیا۔ اسے اپنی راہ میں سب سے بڑی رکاوٹ حضرت امام حسینؓ محسوس ہوئے تھے تو اس نے گورنر مد ینہ کو حکم دیا کہ امام حسین ؓکے پاس جا کر میری بیعت طلب کرو۔ گورنر مدینہ نے حضرت امام حسین ؓکو یزید کا پیغام پہنچایا تو آپ ؓنے صاف انکار کر دیا۔ یہ آپ ؓنے اس لیے کیا کہ آپ ؓ کو اپنے نانا جان حضوراکرمؐ کا فرمان یاد تھا ’’کہ ظالم جابر حکمران کے سامنے کلمہ حق کہنا سب سے بڑا جہاد ہے۔‘‘ تاریخ کے غائر مطالعہ سے جو چیز واضح طور پر ہمارے سامنے آتی ہے وہ یہ ہے...
It is an admitted fact that Islam is “Universal Din” and a complete code of life. Its universality and conciseness is proved from Quran itself. Quran identifies the universality and surmounts it upon all over other Ady┐n and says, “And He sends his messenger along with righteousness and fait Din-e- ╓aq, so that surpass it upon other Dins, though it will be unpleasant for the polytheists”. The Holy verses shows and argues that Dine- Islam is a superior to all other Dins, it may be through love, arguments, conclusiveness or through state and governed on its completion Quran says, “Today I completed your “Din” for you along with all the blessings and liked Islam as a Din for you”. In a nutshell, the above two mentioned the Holy verses indicate clearly the universality and comprehensiveness, because the “Din” which will be superior and must be universal and precise. Islam is the only religion which is beneficial for all mankind in each and every aspect. Its universality is declared that it is a surety for mankind prosperity. Allah says in His Holy Book, “The Holy Quran” that do justice as it is more nearer to piousness. Allah has described “Justice twenty six times His Holy Book and it is also among one of His qualities. All these show the importance of justice.
The explosion of Web based user generated reviews has caused the emergence of Opinion Mining (OM) applications for knowing and analyzing the users‟ opinions toward a product, service, and policy. Opinion mining is getting popular due to rapid growth of web users, increasing number of online discussion forums, and other social media sites. Opinion mining is the process of determining the feelings or opinions of other people about services, politics, products and policies. However, due to the economic importance of these opinions, there is a growing trend of developing efficient and effective opinion mining systems. The main motivation of this thesis is to extract opinion from online blogs and user reviews using lexicon based approach. This work focuses on the development of lexicon based improved term weighting method for polarity classification at sentence level. The polarity lexicons often play a pivotal role in polarity classification of OM, indicating the positivity and negativity of a term along with the numeric score. However, the commonly available domain independent lexicons are not an optimal choice for all domains in OM applications, as polarity of a term changes from one domain to other, and such lexicons do not contain the correct polarity of a term for every domain. In this work, focus is lexicon based polarity classification by adapting a domain dependent polarity lexicon from set of labeled user reviews and domain independent lexicon, and propose a unified learning framework based on information theory concepts that can assign the terms with correct polarity (+ive, -ive) scores. The comparative results obtained from experiments show that proposed method outperforms the other baseline methods (e.g. machine learning methods) and achieves an average accuracy of 79% on word level and 81% at sentence level. The quantitative evaluation of proposed method against baseline methods shows that, (i) for a specific domain proposed method can provide a sufficient coverage of required opinionated text; (ii) adapted domain-specific lexicons have achieved improved performance in a real world and manually built datasets; (iii) polarity classification performance can be improved significantly with resulting adapted lexicon; and (iv) threshold adjustment gives increased accuracy for polarity classification. The proposed framework is quite generalized and capable of classifying the opinionated text in any domain.