Text Mining and Mktg

This study answers marketing scholars' calls for research into understanding the relationship between a firm's engagement activities and the resulting customer engagement using big data: doi.org/10.1016/j.jbusres.20…

Supervised (machine) learning: whatis.techtarget.com/defini…? Useful for anyone interested in artificial intelligence (#AI) and #NLP.

Both software are decent. Many of my colleagues use @apachespark for gigantic data sets, collected from #IoT transactions and social media

Brand ugc of #bigdata valuable->Challenges exist?-> Use Text mining (#LDA and #NLP)->Get Brand Insights->Improve adverts, CRM and innovation

Artificial intelligence won't take over the world, at least in the foreseeable near future, 20 years?

Text mining helps qualitative analysis of marketing #bigdata from #AR and #IoT, but its core methods are quantitative in nature.

Online chatter, #IoT and #bigdata: does online word of mouth impact short term sales? The case of @CocaCola : adage.com/article/cmo-strate…

Sentiment analysis and latent dirichlet allocation give more specific brand-related information out of the Twitter ugc dataset

Artificial intelligence helps solve hunger, poverty, See #IBM recent effort: mashable.com/2017/06/07/ibm-…

Image courtesy of freedigitalphotos.net

The findings from applying latent dirichlet allocation and sentiment analysis are useful for targeted advertising, CRM and brand monitoring.

what is the difference between #IoT and Web 2.0 , Web 3.0 etc?Infrastructure,software,users, mixture of everything?

Being able to automatically derives latent brand topics and classifies brand sentiments is a sign of artificial intelligence

Latent dirichlet allocation uses "big of words",hence ignoring the correlation among documents.This correlation might contain much value

Exploring the psychology of Twitter, big data, text mining, and user generated content.

Machine learning tools show several unique values in deciphering the opinions and feelings of inviduals from #IoT, mobile networks, etc.

Data preprocessing is a critical step before text mining can be used effectively on #bigdata of unstructured text.

When consumers engage brands on Twitter, they mostly talk about product, service, and promotions

Apply text mining with latent Dirichlet allocation (LDA) and sentiment analysis on social #bigdata to derive useful business information.