: You can investigate sentiment classification or language identification in datasets that mix multiple languages (e.g., Hindi-English), which is a growing field in NLP.
To develop a research paper using a dataset, you can leverage several established open-source benchmarks and research repositories that provide diverse, high-scale textual data. Top Datasets for "100K Mixed Text"
: A classic recommendation system dataset containing 100,000 ratings. Researchers often use this to test collaborative filtering and hybrid recommendation algorithms. Download 100K mixed txt
Depending on your research focus (web scraping, social media analysis, or manufacturing), you can download the following 100K-scale datasets:
: Specifically for manufacturing and 3D printing research, this dataset contains over 100,000 G-code files (a form of technical mixed text) along with their corresponding 3D models. Potential Research Directions : You can investigate sentiment classification or language
: This dataset includes over 100,000 textual descriptions of real-life choice dilemmas sourced from social media and surveys, ideal for computational analysis of trade-offs and behavioral themes.
If you need generic "normal English" text in large quantities for training or testing, developers often recommend: Researchers often use this to test collaborative filtering
: A large-scale dataset for LLM-based web information extraction. It combines multilingual markdown/text content from real web pages with natural-language prompts and validated JSON responses.