118 lines
4.1 KiB
Markdown
118 lines
4.1 KiB
Markdown
---
|
|
title: Manohar Gowdru Shridharu
|
|
published: true
|
|
taxonomy:
|
|
category: [phd2024]
|
|
tag: [lm,nlp,hatespeech]
|
|
author: Daniel Hladek
|
|
---
|
|
# Manohar Gowdru Shridharu
|
|
|
|
Beginning of the study: 2021
|
|
|
|
## Disertation Thesis
|
|
|
|
in 2023/24
|
|
|
|
Hate Speech Detection
|
|
|
|
Goals:
|
|
|
|
- Write a dissertaion thesis
|
|
- Publish 2 A-class journal papers
|
|
|
|
## Minimal Thesis
|
|
|
|
(preliminary dissertaion and exam in 2022/23)
|
|
|
|
Goals:
|
|
|
|
- Provide state-of-the-art overview.
|
|
- Formulate dissertation theses (describe scientific contribution of the thesis).
|
|
- Prepare to reach the scientific contribution.
|
|
- Publish 4 conference papers.
|
|
|
|
## First year of PhD study
|
|
|
|
Goals:
|
|
|
|
- Provide state-of-the-art overview.
|
|
- Read and make notes from at least 100 scientific papers or books.
|
|
- Publish at least 2 conference papers.
|
|
- Prepare for minimal thesis.
|
|
|
|
Resources:
|
|
|
|
- [Hate Speech Project Page](/topics/hatespeech)
|
|
- https://hatespeechdata.com/
|
|
- [Hate speech detection: Challenges and solutions](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701757/)
|
|
- [HateBase](https://hatebase.org/)
|
|
- [Resources and benchmark corpora for hate speech detection: a systematic review](https://link.springer.com/article/10.1007/s10579-020-09502-8)
|
|
|
|
### Meeting 10.1.22
|
|
|
|
- Set up a git account https://github.com/ManoGS with script to prepare "twitter" dataset and "english" dataset for HS detection.
|
|
- confgured laptop with (Anaconda) / PyCharm, pytorch, cuda gone throug some basic python tutorials.
|
|
- Read some blogs how to use kaggle (dataset database).
|
|
- tutorials on huggingface transformers - understanding sentiment analysis.
|
|
|
|
|
|
#### Meeting 16.12.21
|
|
|
|
- A report was provided (through Teams).
|
|
- Installed Anaconda and started s Transformers tutorial
|
|
- Started Dive into python book
|
|
|
|
Task:
|
|
|
|
- Report: Create a detailed list of available datasets for HS.
|
|
- Report: Create a detailed description of the state of the art approaches for HS detection.
|
|
- Practical: Continue with open tasks below. (pick datasetm, perform classification,evaluate the experiment.)
|
|
|
|
|
|
#### Meeting 10.12.21
|
|
|
|
No report (just draft) was provided so far.
|
|
|
|
1. Read papers from below and make notes what you have learned fro the papers. For each note make a bibliographic citation. Write down authors of the paper, name paper of the paper, year, publisher and other important information.
|
|
When you find out something, make a reference with a number to that paper.
|
|
You can use a bibliografic manager software. Mendeley, Endnote, Jabref.
|
|
2. From the papers find out answers to the questions below.
|
|
3. Pick a hatespeech dataset.
|
|
4. Pick an approach and Python library for HS classification.
|
|
5. Create a [GIT](https://git.kemt.fei.tuke.sk) repository and share your experiment files. Do not commit data files, just links how to download the files.
|
|
6. Perform and evaluate experiments.
|
|
|
|
#### Meeting 10.11.21
|
|
|
|
#### First tasks
|
|
|
|
Prepare a report where you will explain:
|
|
|
|
- what is hate speech detection,
|
|
- where and why you can use hate-speech detection,
|
|
- what are state-of-the-art methods for hate speech detection,
|
|
- how can you evaluate a hate-speech detection system,
|
|
- what datasets for hate-speech detection are available,
|
|
|
|
The report should properly cite scientific bibliographical sources.
|
|
Use a bibliography manager software, such as Mendeley.
|
|
|
|
Create a [VPN connection](https://uvt.tuke.sk/wps/portal/uv/sluzby/vzdialeny-pristup-vpn) to the university network to have access to the scientific databses. Use scientific indexes to discover literature:
|
|
|
|
- [Scopus](https://www.scopus.com/) (available from TUKE VPN)
|
|
- [Scholar](httyps://scholar.google.com)
|
|
|
|
Your review can start with:
|
|
|
|
- [Hate speech detection: Challenges and solutions](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701757/)
|
|
- [HateBase](https://hatebase.org/)
|
|
- [Resources and benchmark corpora for hate speech detection: a systematic review](https://link.springer.com/article/10.1007/s10579-020-09502-8)
|
|
|
|
Get to know the Python programming language
|
|
|
|
- Read [Dive into Python](https://diveintopython3.net/)
|
|
- Install [Anaconda](https://www.anaconda.com/)
|
|
- Try [HuggingFace Transformers library]( https://huggingface.co/transformers/quicktour.html)
|
|
|