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A sentiment-based chat bot
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Natural language processing is a field in computer science which involves

making computers derive meaning from human language and input as

a way of interacting with the real world. Broadly speaking, sentiment

analysis is the act of determining the attitude of an author or speaker,

with respect to a certain topic or the overall context and is an application

of the natural language processing field.

This essay discusses the implementation of a Twitter chat bot that uses

natural language processing and sentiment analysis to construct a believable

reply. This is done in the Python programming language, using

a statistical method called Naive Bayes classifying supplied by the NLTK

Python package. The essay concludes that applying natural language

processing and sentiment analysis in this isolated fashion was simple,

but achieving more complex tasks greatly increases the difficulty.

Abstract [sv]

Natural language processing är ett fält inom datavetenskap som innefattar

att få datorer att förstå mänskligt språk och indata för att på så

sätt kunna interagera med den riktiga världen. Sentiment analysis är,

generellt sagt, akten av att försöka bestämma känslan hos en författare

eller talare med avseende på ett specifikt ämne eller sammanhang och

är en applicering av fältet natural language processing.

Den här rapporten diskuterar implementeringen av en Twitter-chatbot

som använder just natural language processing och sentiment analysis

för att kunna svara på tweets genom att använda känslan i tweetet.

Detta görs i programmeringsspråket Python med en statistisk metod

kallad Naive Bayes classifying med hjälp av Python-paketet NLTK.

Rapporten gör slutsatsen att appliceringen av natural language processing

och sentiment analysis är enkelt när det görs inom detta isolerade

område, men att utföra mer komplexa uppgifter ökar svårighetsgraden

markant.

Place, publisher, year, edition, pages
2013.
Series
Kandidatexjobb CSC, K13048
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-136134OAI: oai:DiVA.org:kth-136134DiVA: diva2:670679
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2013-12-13 Created: 2013-12-03 Last updated: 2013-12-13Bibliographically approved

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A sentiment-based chat bot(367 kB)332 downloads
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File name FULLTEXT01.pdfFile size 367 kBChecksum SHA-512
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Type fulltextMimetype application/pdf

Other links

http://www.csc.kth.se/utbildning/kth/kurser/DD143X/dkand13/Group8Anna/report/TwitterBot_AlexanderSofie.pdf
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School of Computer Science and Communication (CSC)
Computer Science

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CiteExportLink to record
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Citation style
  • apa
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Output format
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