Latent Dirichlet Allocation (LDA) Topic Modelling for Library Science Dissertation
Budget: £250 – £750 GBP
I'm looking to analyze a corpus of four Word documents (consisting of 39, 40, 30 and 30 pages) for my Masters' dissertation in Library and Information Science. I intend for an expert to apply Latent Dirichlet Allocation (LDA) topic modelling to help reveal the hidden thematic structure within these documents.
I don't have the software or computing know-how to run LDA using Gensim in Python. The freelancer needs to use Gensim.
Key responsibilities:
- Preprocessing the dataset, including text cleaning and formatting
- Applying LDA topic modeling algorithm to the dataset
- Interpreting the results and grouping documents by topics
- Allowing for adjustments based on my input and requirements
- Ensuring procedure is well-documented for reference in my academic work
Ideal skills and experience:
- Deep understanding of Natural Language Processing (NLP) and experience with topic modelling, specifically LDA
- Extensive experience in preparing and processing large text data
- Proficient in utilizing libraries for handling Word documents
- Strong analytical thinking and data interpretation skills
- Capability to work within academic guidelines and standards
While my project is scholarly, I want the project's findings to be as clear and approachable as possible. An ideal freelancer would be able to communicate frequently and be open to a collaborative approach.
Credit will be given for the freelancer who works on the project. Need a fast turnaround, must be completed within 7 days.
I don't have the software or computing know-how to run LDA using Gensim in Python. The freelancer needs to use Gensim.
Key responsibilities:
- Preprocessing the dataset, including text cleaning and formatting
- Applying LDA topic modeling algorithm to the dataset
- Interpreting the results and grouping documents by topics
- Allowing for adjustments based on my input and requirements
- Ensuring procedure is well-documented for reference in my academic work
Ideal skills and experience:
- Deep understanding of Natural Language Processing (NLP) and experience with topic modelling, specifically LDA
- Extensive experience in preparing and processing large text data
- Proficient in utilizing libraries for handling Word documents
- Strong analytical thinking and data interpretation skills
- Capability to work within academic guidelines and standards
While my project is scholarly, I want the project's findings to be as clear and approachable as possible. An ideal freelancer would be able to communicate frequently and be open to a collaborative approach.
Credit will be given for the freelancer who works on the project. Need a fast turnaround, must be completed within 7 days.