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Social Media Research

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Automated text analysis

Automated text analysis is a powerful internet research tool. It allows you to summarize and analyze topics of discussions, extract key ideas, predict attitudes and reactions, and discover hidden psychological patterns.

A number of software is designed for Automated text analysis, namely: LIWC, SAS Text Miner, IBM Watson, Meaning Cloud, MEM, Lexalytics, SPSS Modeler Text analytics, Amazon Comprehend, Google Cloud Natural Language, Rosette Text Analytics Platform, Cat Coding Analysis Toolkit, Angoos Knowledge Reader etc.

The key purposes of Automated text analysis are:

MARKETING: research of target customers and demand

Read our review of Automated text analysis tools
  • Target customers’ identification;
  • Customers experience of targeted products or services;
  • Customer personal goals and values;
  • Educational, cultural and intellectual level;
  • Recurrent interests and hobbies;
  • Explicit patterns of thinking / behavior;
  • Psychological traits of personality.


Automated text analysis of students postings on Social Media allows us to understand:

  • Critical view of students on the learning process;
  • Overall students perception on Education Service Providers (Universities, Colleges, Schools, etc)
  • Hobbies and interests;
  • Relations with friends and classmates;
  • Cognitive or psychological problems;
  • Motivational and learning problems;
  • Professional and educational orientation;


Automated text analysis of employees in any particular company allows us to determine:

  • Working atmosphere in the company;
  • Corporate problems discussed;
  • Employees turnover;
  • Brand / product reputation in Social media;
  • Customers complaints.


  • Identify new business / social trends, based on Internet activity, what can be considered as early indicators;
  • Growing demand identification based on search queries and Social media discussions;
  • Growing supply identification, based on websites’ metrics, SEO and AdWords activities and Social Media advertising and discussions;
  • Get insights on stock market traders’ discussions and sentiment analysis;


Automated text analysis helps to:

  • Find prospective candidates;
  • Analyze and prove both their professional and personal background;
  • Identify possible misinformation in CVs and other documents;
  • Analyze individual social network of a candidate (graph analysis);
  • Understand hidden psychological patterns as well as professional orientation;


Automated text analysis helps to:

  • Indicate new social and cultural trends in their early stages;
  • Text analysis (opinions, discussions, search queries) can be compared with demographic analysis of Social Media: changes of personal status (marital, location, job, education etc.);
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