Topic modeling using latent Dirichlet allocation: A survey
We are not able to deal with a mammoth text corpus without summarizing them into a
relatively small subset. A computational tool is extremely needed to understand such a …
relatively small subset. A computational tool is extremely needed to understand such a …
Large-scale computerized text analysis in political science: Opportunities and challenges
Text has always been an important data source in political science. What has changed in
recent years is the feasibility of investigating large amounts of text quantitatively. The internet …
recent years is the feasibility of investigating large amounts of text quantitatively. The internet …
Interpretable machine learning-based approach for customer segmentation for new product development from online product reviews
For new product development, previous segmentation methods based on demographic,
psychographic, and purchase behavior information cannot identify a group of customers with …
psychographic, and purchase behavior information cannot identify a group of customers with …
Applications of topic models
How can a single person understand what's going on in a collection of millions of
documents? This is an increasingly common problem: sifting through an organization's e …
documents? This is an increasingly common problem: sifting through an organization's e …
Utilizing big data analytics for information systems research: challenges, promises and guidelines
This essay discusses the use of big data analytics (BDA) as a strategy of enquiry for
advancing information systems (IS) research. In broad terms, we understand BDA as the …
advancing information systems (IS) research. In broad terms, we understand BDA as the …
Cross-lingual contextualized topic models with zero-shot learning
Many data sets (eg, reviews, forums, news, etc.) exist parallelly in multiple languages. They
all cover the same content, but the linguistic differences make it impossible to use traditional …
all cover the same content, but the linguistic differences make it impossible to use traditional …
[PDF][PDF] Text mining for information systems researchers: An annotated topic modeling tutorial
Abstract t is estimated that more than 80 percent of today's data is stored in unstructured
form (eg, text, audio, image, video); and much of it is expressed in rich and ambiguous …
form (eg, text, audio, image, video); and much of it is expressed in rich and ambiguous …
[책][B] Text as data: A new framework for machine learning and the social sciences
A guide for using computational text analysis to learn about the social world From social
media posts and text messages to digital government documents and archives, researchers …
media posts and text messages to digital government documents and archives, researchers …
Content analysis of e-petitions with topic modeling: How to train and evaluate LDA models?
L Hagen - Information Processing & Management, 2018 - Elsevier
E-petitions have become a popular vehicle for political activism, but studying them has been
difficult because efficient methods for analyzing their content are currently lacking …
difficult because efficient methods for analyzing their content are currently lacking …
Mining the voice of employees: A text mining approach to identifying and analyzing job satisfaction factors from online employee reviews
Y Jung, Y Suh - Decision Support Systems, 2019 - Elsevier
Online reviews have become a significant information source for business practitioners to
know about customers' opinions of their products or services. Previous studies examined …
know about customers' opinions of their products or services. Previous studies examined …