Semantic analysis in Newspoint

25 January 2022, Robert Sadowski

Newspoint offers semantic analysis of monitored articles, posts, advice and reviews. Because semantics is concerned with describing the meaning of phrases, sentences, and long texts, its application allows marketers to better understand what users think about their products and services. Manual analysis has been expanded to include automatic methods of the NLP classes, Clustering, Text Mining, Artificial Intelligence and Natural Language Modeling.

The multitude of reviews, opinions and recommendations that users leave on blogs, forums and social platforms make the Internet a source of valuable information about specific products, models and services. The more data available, the more conclusions can be drawn and the better their statistical accuracy.

Product reviews and user experiences are an excellent basis for market research. These test may be carried out on:

  • Image questions, sound analyses – getting to know the emotional attitude towards the brand
  • Analysis of the demographic profile of consumers
  • Assessment of consumer behaviour
  • Investigation of the reception of advertising campaigns
  • Results of the advertising activities carried out (before and after the campaigns)  
  • Contexts of the statements
  • Identification of market trends
  • Demand surveys for new products/services
  • Product development with new functionalities

Such a study involves the categorization of a sample (or all instances) of publications selected according to a prepared set of keywords. The advantage of the method is the analysis of spontaneous, unmoderated statements by Internet users, who usually speak honestly about a particular offer. Qualitative research makes it possible to identify the most relevant topics. However, the large amount of data presents problems in terms of quick manual analysis and accurate interpretation.

The Newspoint team has implemented automated semantic analysis methods to analyze sentiment in detail and accurately evaluate the meaning of words, phrases, whole sentences and feedback texts. Technologies from the fields of semantic tagging, clustering, semantic search engine engines, text analysis (so-called text mining), language dictionaries and AI were used.

Clustering
Clustering
Semantic tags
Semantic tags
Negative sentimental phrases
Negative sentimental phrases

The benefits of semantic content analysis for your company:

  • thematic grouping, i.e. what exactly associates your brand / product / service / media communication
  • extraction of clusters and semantic tags (sentences defining content topics)  
  • get a list of positive and negative sentimental phrases (assessments and opinions) on a specific topic
  • knowledge of the setting according to sources and authors of the publication texts
  • sentiment changes over time
  • separation of the main problems and advantages of a particular offer or product
  • correlation of problems encountered and widespread
  • sentiment comparison: Your brand against your competition

We invite all those who are interested in the semantic analysis of texts and opinions to contact us.



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