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TRAC: Language Analysis

Discover the full range of language analysis capabilities on Pulsar TRAC and how they can be beneficial to your social listening efforts.

Updated over a week ago

Learning Outcomes:

  • Learn about TRAC's language coverage and its capabilities.

  • Understand how language analysis can help you identify sentiment, topics, and entities.

  • Discover the benefits of TRAC's multilingual capabilities.

  • Explore the ways TRAC's language analysis can aid in cross-cultural understanding.


TRAC's Language Coverage

TRAC supports various languages, including commonly spoken languages like English, French, and Spanish, as well as less common ones like Icelandic and Urdu. This means that TRAC can help you analyse online conversations in a wide range of languages, providing you with a comprehensive view of the online discussions happening around your topics of interest. These multilingual capabilities allow you to analyse social conversations in a wide range of languages, without needing to manually translate them. This saves time and allows you to analyse conversations in real-time, regardless of the language they are in.


Sentiment, Emotion, Topics and Entities extraction is supported in the following languages:

  1. Afrikaans

  2. Albanian

  3. Amharic

  4. Arabic

  5. Armenian

  6. Azerbaijani

  7. Basque

  8. Breton

  9. Bulgarian

  10. Burmese

  11. Catalan

  12. Chinese Simplified

  13. Chinese Traditional

  14. Croatian

  15. Czech

  16. Danish

  17. Dutch

  18. English

  19. Esperanto

  20. Estonian

  21. Faroese

  22. Fijian

  23. Finnish

  24. French

  25. Georgian

  26. German

  27. Greek

  28. Hausa

  29. Hebrew

  30. Hindi

  31. Hungarian

  32. Icelandic

  33. Indonesian

  34. Irish

  35. Italian

  36. Japanese

  37. Korean

  38. Latin

  39. Latvian

  40. Lithuanian

  41. Macedonian

  42. Malay

  43. Maltese

  44. Maori

  45. Nepali

  46. Norwegian

  47. Persian

  48. Polish

  49. Portuguese

  50. Romanian

  51. Russian

  52. Serbian

  53. Shona

  54. Slovak

  55. Slovenian

  56. Spanish

  57. Swahili

  58. Swedish

  59. Tagalog

  60. Tamil

  61. Thai

  62. Turkish

  63. Ukrainian

  64. Urdu

  65. Vietnamese

  66. Welsh

  67. Wolof

  68. Xhosa


TRAC's Language Analysis Capabilities

TRAC's language analysis capabilities are extensive and can you help you to extract a wide range of insights from the discussions taking place online. With the use of NLP, our language analysis goes beyond simple detection and can analyse the common keywords, topics, sentiment, entities and emotion found in an article or media clip. This can help you gain cross-cultural understanding and a better view of the conversations happening in different parts of the world. So, when we talk about language analysis on Pulsar, we are talking about the ability to detect the language, and the ability to analyse the sentiment, emotion, topics and entities found in a content, regardless of the language.

Sentiment Analysis

TRAC can identify the sentiment behind social conversations and help you understand how people feel about your brand or a specific topic. This can be particularly helpful for monitoring brand reputation and identifying issues before they escalate. If you want to learn more about Sentiment Analysis on TRAC, then use the link below.


Emotion Analysis

Emotion Analysis is a standard part of natural language processing and involves analyzing the underlying emotions expressed in text. These emotions can range from joy, excitement and surprise to fear, hate and disgust. If you want to learn more about Emotion Analysis on TRAC, then use the link below.


Topics Analysis

Using a top-down taxonomy approach, TRAC can identify the key themes found in conversations in a range of languages, even if they aren’t explicitly mentioned, helping you to understand what people are talking about and identify emerging trends. If you want to learn more about Topics Analysis on TRAC then use the link below.


Entities Analysis

Named Entity Recognition (NER) is a subtask of Natural Language Processing (NLP) and as the name suggests, is the process of identifying and classifying units (named entities), in a given text. And these entities can be words or phrases that represent names of people, names of organisations, places, products, etc. TRAC can identify specific entities mentioned in online conversations across a range of languages. If you want to learn more about Entities, then you can click on the button below.


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