Pbm: A new dataset for blog mining
Mehwish Aziz, Muhammad Rafi

TL;DR
This paper introduces a new dataset for Pakistani political blogs to facilitate research in blog mining, addressing the scarcity of standard datasets for this emerging web genre.
Contribution
It presents the collection, organization, and standardization of a novel blog dataset specifically for Pakistani political blogs, enabling various text mining applications.
Findings
Dataset enables blog-search and sentiment analysis
Facilitates identification of influential bloggers
Supports clustering of blog posts
Abstract
Text mining is becoming vital as Web 2.0 offers collaborative content creation and sharing. Now Researchers have growing interest in text mining methods for discovering knowledge. Text mining researchers come from variety of areas like: Natural Language Processing, Computational Linguistic, Machine Learning, and Statistics. A typical text mining application involves preprocessing of text, stemming and lemmatization, tagging and annotation, deriving knowledge patterns, evaluating and interpreting the results. There are numerous approaches for performing text mining tasks, like: clustering, categorization, sentimental analysis, and summarization. There is a growing need to standardize the evaluation of these tasks. One major component of establishing standardization is to provide standard datasets for these tasks. Although there are various standard datasets available for traditional text…
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Taxonomy
TopicsWeb Data Mining and Analysis · Sentiment Analysis and Opinion Mining · Advanced Text Analysis Techniques
