| SGF |
2020 |
Exploring Online Drug Reviews using Text Analytics, Sentiment Analysis, and Data Mining Models |
Thu Dinh,
Goutam Chakraborty |
source |
23 |
| SGF |
2020 |
Sound Insights: A Pipeline for Information Extraction from Audio Files |
Biljana Belamaric Wilsey,
Xiaozhuo Cheng |
source |
8 |
| PharmaSUG |
2020 |
Detecting Side Effects and Evaluating the Effectiveness of Drugs from Customers' Online Reviews using Text Analytics, Sentiment Analysis and Machine Learning Models |
Thu Dinh,
Goutam Chakraborty |
source |
22 |
| SESUG |
2019 |
Analyzing Airbnb reviews using SAS Text Miner and Predicting the factors contributing for higher ratings |
Ashlesha Sampathi |
source |
15 |
| MWSUG |
2019 |
Detecting Side Effects and Evaluating Effectiveness of Drugs from Customers' Online Reviews using Text Analytics and Data Mining Models |
Thu Dinh |
|
23 |
| WUSS |
2019 |
Analyzing Factors Influencing Viewer Count of TED Talks through Text Analytics |
Yasha Pastaria |
source |
15 |
| SGF |
2019 |
Influencer Marketing Analytics Using SAS Viya |
Tamas Bosznay |
source |
19 |
| SESUG |
2018 |
A Case Study of Mining Social Media Data for Disaster Relief: Hurricane Irma |
Hurricane Irma |
source |
11 |
| SESUG |
2018 |
Fight Human Trafficking with Text Analytics |
Stuti Mehrotra,
Miriam McGaugh |
source |
10 |
| SESUG |
2018 |
Text Mining to Predict College Admission Trends |
Shashikant Chebrolu |
source |
11 |
| MWSUG |
2018 |
Analyzing Amazon's Customer Reviews using SAS Text Miner for Devising Successful Product Launch Strategies |
Manideep Mellachervu,
Anvesh Reddy Minukuri |
|
13 |
| MWSUG |
2018 |
Analyzing YouTube comments on gun violence using SAS Viya and SAS Text Miner |
Sridevi Loya |
|
9 |
| SGF |
2018 |
A Case Study of Mining Social Media Data for Disaster Relief: Hurricane Irma |
Bogdan Gadidov,
Linh H. Le |
source |
11 |
| SGF |
2018 |
Flight 3411 and Its Aftermath: A Burlesque Analysis via Tweets |
Vinoth Kumar Raja,
Padmashri Janarthanam |
source |
22 |
| SGF |
2018 |
From Unstructured Text to the Data Warehouse: Customer Support at the University of North Texas |
Nick Evangelopoulos |
source |
10 |
| SGF |
2018 |
Harvesting Unstructured Data to Reduce Anti-Money Laundering (AML) Compliance Risk |
Austin Cook,
Beth Herron |
source |
10 |
| SGF |
2018 |
Sentiment Analysis of Netflix and Competitor Tweets to Classify Customer Opinions |
Rucha Jadhavar,
Agastya Komarraju |
source |
15 |
| SGF |
2018 |
Sentiment Analysis on YouTube Movie Trailer Comments to Determine the Impact on Box-Office Earnings |
Rishanki Jain |
source |
9 |
| SGF |
2018 |
Using SAS Enterprise Miner for Categorization of Customer Comments to Improve Services at USPS |
Olayemi Olatunji |
source |
7 |
| SESUG |
2017 |
Analysis of Tweets on Demonetization in India using SAS Enterprise Miner |
Jital Patel,
Narmada Deve Panneerselvam |
source |
19 |
| SESUG |
2017 |
Understanding the influence of the day of the week in the reviews written using SAS Enterprise Miner TM and SAS Sentiment Analysis Studio |
Sujal Reddy Alugubelli |
source |
10 |
| SESUG |
2017 |
Using SAS Enterprise Miner for Categorization of Customer Comments to Improve Services at the U.S. Postal Service |
Olayemi Olatunji,
United States Postal |
source |
7 |
| SCSUG |
2017 |
Apple or Samsung? Which Phone Should I Buy? Sentiment Analysis Utilizing Customer Reviews on Unlocked iPhone and Samsung Galaxy |
Rosie Nguyen,
Nandan Moza,
Goutam Chakraborty,
Miriam McGaugh |
source |
14 |
| SCSUG |
2017 |
Classifying and Predicting Spam Messages Using Text Mining in SAS Enterprise Miner |
Venkata Kondamudi,
Sai Mounika,
Balamurugan Mohan |
source |
14 |
| SCSUG |
2017 |
Sentiment Analysis on YouTube Movie Trailer Comments to Determine the Impact on Box-Office Earnings |
Rishanki Jain |
source |
9 |
| SCSUG |
2017 |
Text Mining on Donor's Conversation with Solicitors |
Harsh Gupta |
source |
12 |
| SCSUG |
2017 |
Using SAS Enterprise Miner for Categorization of Customer Comments to Improve Services at the U.S. Postal Service |
Olayemi Olatunji |
source |
8 |
| SCSUG |
2017 |
Which smartphone would you choose? |
Mohana Krishna Chaitanya Korlepara,
Miriam McGaugh,
Goutam Chakraborty |
source |
15 |
| WUSS |
2017 |
Using SAS Enterprise Miner for Categorization of Customer Comments to Improve Services at the U.S. Postal Service |
Olayemi Olatunji |
source |
7 |
| SGF |
2017 |
Behavioral Spend Modeling of Cheque Card Data Using SAS Text Miner |
Amelia Van Schalkwyk |
source
pdf |
14 |
| SGF |
2017 |
How Members Really Feel About Your Credit Card |
Anirban Chakraborty,
Surya Bhaskar Ayyalasomayajula |
source |
25 |
| SGF |
2017 |
Mind-Map the Gap: Sentiment Analysis of Public Transport |
Tamas Bosznay |
source |
20 |
| SGF |
2017 |
Using Text Analysis to Improve the Quality of Scoring Models with SAS Enterprise Miner |
Piotr Małaszek |
source |
11 |
| SGF |
2017 |
Visualizing Market Structure Using Brand Sentiments |
Praveen Kumar Kotekal,
Amit K Ghosh,
Goutam Chakraborty |
source |
9 |
| SCSUG |
2016 |
Analyzing sentiments in tweets for Tesla Model 3 |
Praneth Guggilla,
Tejaswi Jha,
Goutam Chakraborty |
source |
12 |
| SCSUG |
2016 |
Categorization of Fitbit's Customer Complaints on Twitter |
Sapna Bhoir,
Jacky Arora |
source |
17 |
| SCSUG |
2016 |
Enabling news trading by automatic categorisation of news articles |
Praveen Kumar Kotekal,
Vishwanath Kolar Bhaskara |
source |
9 |
| SCSUG |
2016 |
Sentiment Analysis of Opinions about Self Driving Cars |
Nachiket Kawitkar,
Swapneel Deshpande,
Goutam Chakraborty,
Miriam McGaugh |
source |
13 |
| SESUG |
2016 |
Text mining and sentiment analysis on video game user reviews using SAS Enterprise Miner |
Mukesh Kumar Singh,
Nikhil Batti,
Miriam McGaugh |
source |
13 |
| MWSUG |
2016 |
Analyzing sentiments in tweets for Tesla Model 3 using SAS Enterprise Miner and SAS Sentiment Analysis Studio |
Tejaswi Jha,
Praneth Guggilla |
|
12 |
| WUSS |
2016 |
Categorization of Fitbit's Customer Complaints on Twitter |
Jacky Arora,
Sapna Bhoir |
source |
17 |
| WUSS |
2016 |
Descriptive Analysis of Donation Amount Data and Text Mining of Tweets on Presidential Primaries using SAS |
Aditya Jakkam,
Swetha Nallamala |
source |
14 |
| SGF |
2016 |
Analysis of IMDb Reviews for Movies and Television Series Using SAS Enterprise Miner and SAS Sentiment Analysis Studio |
Ameya Jadhavar,
Goutam Chakraborty,
Prithvi Raj Sirolikar |
source |
17 |
| SGF |
2016 |
Text Analytics and Brand Topic Maps |
Nicholas Evangelopoulos |
source |
11 |
| SGF |
2016 |
Using SAS Text Miner for Automatic Categorization of Blog Posts on a Social Networking Site Dedicated to Cyclists |
Heramb Joshi,
Goutam Chakraborty |
source |
11 |
| SGF |
2015 |
Alien Nation: Text Analysis of UFO Sightings in the US Using SAS Enterprise Miner 13.1 |
Pradeep Reddy Kalakota,
Naresh Abburi,
Goutam Chakraborty,
Zabiulla Mohammed |
source
zip |
14 |
| SGF |
2015 |
Using Text from Repair Tickets of a Truck Manufacturing Company to Predict Factors that Contribute to Truck Downtime |
Ayush Priyadarshi,
Goutam Chakraborty |
source |
9 |
| WUSS |
2014 |
Expediting Access to Critical Pathology Data |
Leanne Goldstein,
Rebecca Ottesen,
Julie A. Kilburn,
Joyce C. Niland |
source |
8 |
| PharmaSUG |
2014 |
Expediting Access to Critical Pathology Data |
Rebecca Ottesen,
Leanne Goldstein,
Julie A. Kilburn,
Joyce C. Niland |
source |
8 |
| SGF |
2014 |
Automatic Detection of Section Membership for SAS Conference Paper Abstract Submissions: A Case Study |
Goutam Chakraborty,
Murali Krishna Pagolu |
source |
13 |
| SGF |
2014 |
Text Mining Economic Topic Sentiment for Time Series Modeling |
Michael P. Dessauer,
Justin Kauhl |
source |
14 |
| SESUG |
2013 |
Binning Bombs When You're Not a Bomb Maker: A Code-Free Methodology to Standardize, Categorize, and Denormalize Categorical Data |
Binning Bombs |
source |
26 |
| SGF |
2013 |
Investigating the Impact of Amazon Kindle Fire HD 7? on Amazon.com Consumers Using SAS Text Miner and SAS Sentiment Analysis View Paper View Poster |
Goutam Chakraborty,
Hari Hara Sudhan Duraidhayalu,
Srihari Nagarajan |
source
pdf |
14 |
| SGF |
2013 |
Relate, Retain, and Remodel: Creating and Using Context-Sensitive Linguistic Features in Text Mining Models |
Janardhana Punuru,
Lane Surratt,
Russell Albright |
source |
17 |
| SGF |
2013 |
Replacing Manual Coding of Customer Survey Comments with Text Mining: A Story of Discovery with Textual Data in the Public Sector |
Jared Prins |
source |
19 |
| SGF |
2012 |
Twitter and Facebook Analysis: Its Not Just for Marketing Anymore |
Jodi Blomberg |
source |
9 |
| SEUGI |
2003 |
Using SAS Text Miner to extract intelligence from unstructured text sources [presentation] |
Bernd Drewes,
Manya Mayes |
source |
29 |
| SEUGI |
2001 |
The SAS Text Mining Solution [presentation] |
Bernd Drewes,
Wayne Thompson |
source |
22 |
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