Generating Business Intelligence Through Social Media Analytics: Measuring Brand Personality with Consumer-, Employee-, and Firm-Generated Content

2018 ◽  
Author(s):  
Yuheng Hu ◽  
Yili Hong ◽  
David Gal ◽  
Anbang Xu ◽  
Vibha Sinha ◽  
...  
Keyword(s):  
Social Media ◽  
Business Intelligence ◽  
Brand Personality ◽  
Social Media Analytics

Social media analytics and business intelligence research: A systematic review

2020 ◽  
Vol 57 (6) ◽  
pp. 102279
Author(s):  
Jaewoong Choi ◽  
Janghyeok Yoon ◽  
Jaemin Chung ◽  
Byoung-Youl Coh ◽  
Jae-Min Lee
Keyword(s):  
Systematic Review ◽  
Social Media ◽  
Business Intelligence ◽  
Social Media Analytics

Interaction Mining

2012 ◽  
pp. 688-709
Author(s):  
Vincenzo Pallotta ◽  
Lammert Vrieling ◽  
Rodolfo Delmonte
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Future Development ◽  
Business Intelligence ◽  
Relationship Management ◽  
Marketing Research ◽  
Customer Relationship ◽  
Unstructured Data ◽  
Social Media Analytics ◽  
Business Analytics

In this chapter we present the major challenges of a new trend in business analytics, namely Interaction Mining. With the proliferation of unstructured data as the result of people interacting with each other using digital networked devices, classical methods in text business analytics are no longer effective. We identified the causes of their failure as being related to the inadequacy of dealing with conversational data. We propose then to move from Text Mining towards Interaction Mining, and we make several cases for this transition in areas such as marketing research, social media analytics, and customer relationship management. We also propose a roadmap for the future development of Interaction Mining by challenging the current practices in business intelligence and information visualization.

Interaction Mining

2011 ◽  
pp. 122-146 ◽  
Author(s):  
Vincenzo Pallotta ◽  
Lammert Vrieling ◽  
Rodolfo Delmonte
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Future Development ◽  
Business Intelligence ◽  
Relationship Management ◽  
Marketing Research ◽  
Customer Relationship ◽  
Unstructured Data ◽  
Social Media Analytics ◽  
Business Analytics

In this chapter we present the major challenges of a new trend in business analytics, namely Interaction Mining. With the proliferation of unstructured data as the result of people interacting with each other using digital networked devices, classical methods in text business analytics are no longer effective. We identified the causes of their failure as being related to the inadequacy of dealing with conversational data. We propose then to move from Text Mining towards Interaction Mining, and we make several cases for this transition in areas such as marketing research, social media analytics, and customer relationship management. We also propose a roadmap for the future development of Interaction Mining by challenging the current practices in business intelligence and information visualization.

scholarly journals Social Media Analytics

2021 ◽  
pp. 396-401
Author(s):  
Riya M. Hate ◽  
Vaishnavi T. Naik
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Data Collection ◽  
Data Storage ◽  
Business Intelligence ◽  
Social Media Analytics ◽  
Business Activity ◽  
Planning Strategy ◽  
Collection Data ◽  
Research Decision

Social media is a broad spectrum of process like data collection, data storage into databases and preparation of data which is utilized for research, decision making, marketing campaign with the aid of various tools and algorithms to measure the performance of a product. Analyzing social media to collect data and planning strategy around them has become one of the major business activity. Topics covered in this papers would be applications and impact of social media, challenges faced while retrieving data and preparing data for business intelligence, it also mentions some tools and algorithm.

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