Research on Sentiment Analysis: The First Decade

Oskar Ahlgren

doi:10.1109/ICDMW.2016.0131

Research on Sentiment Analysis: The First Decade

Oskar Ahlgren^*

^*Tämän työn vastaava kirjoittaja

Tieto- ja palvelujohtamisen laitos

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

6 Viittaukset (Web of Science)

Abstrakti

The first publications on sentiment analysis and opinion mining were published roughly a decade ago. Now it is time to lookback on the achievements so far. This paper presents statistics on the evolution of sentiment analysis. What kind of topics have beendiscussed? How has their popularity changed over time? Who have been the leading researchers? Answers to these questions areprovided by statistical analysis on keywords and by applying Latent Dirichlet Allocation to the titles and abstracts of the publications. The aim of this paper is to provide background information on the big picture of semantic analysis and its development over time.

Alkuperäiskieli	Englanti
Otsikko	Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
Kustantaja	IEEE
Sivut	890-899
Sivumäärä	10
ISBN (elektroninen)	9781509054725
DOI - pysyväislinkit	https://doi.org/10.1109/ICDMW.2016.0131
Tila	Julkaistu - 30 tammik. 2017
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	IEEE International Conference on Data Mining Workshops - Barcelona, Espanja Kesto: 12 jouluk. 2016 → 15 jouluk. 2016

Conference

Conference	IEEE International Conference on Data Mining Workshops
Lyhennettä	ICDMW
Maa/Alue	Espanja
Kaupunki	Barcelona
Ajanjakso	12/12/2016 → 15/12/2016

Pääsy asiakirjaan

10.1109/ICDMW.2016.0131

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Link to publication in Scopus

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title = "Research on Sentiment Analysis: The First Decade",

abstract = "The first publications on sentiment analysis and opinion mining were published roughly a decade ago. Now it is time to lookback on the achievements so far. This paper presents statistics on the evolution of sentiment analysis. What kind of topics have beendiscussed? How has their popularity changed over time? Who have been the leading researchers? Answers to these questions areprovided by statistical analysis on keywords and by applying Latent Dirichlet Allocation to the titles and abstracts of the publications. The aim of this paper is to provide background information on the big picture of semantic analysis and its development over time.",

keywords = "Latent Dirichlet Allocation, Literature Study, Sentiment Analysis",

author = "Oskar Ahlgren",

year = "2017",

month = jan,

day = "30",

doi = "10.1109/ICDMW.2016.0131",

language = "English",

pages = "890--899",

booktitle = "Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016",

publisher = "IEEE",

address = "United States",

note = "IEEE International Conference on Data Mining Workshops, ICDMW ; Conference date: 12-12-2016 Through 15-12-2016",

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T2 - IEEE International Conference on Data Mining Workshops

AU - Ahlgren, Oskar

PY - 2017/1/30

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N2 - The first publications on sentiment analysis and opinion mining were published roughly a decade ago. Now it is time to lookback on the achievements so far. This paper presents statistics on the evolution of sentiment analysis. What kind of topics have beendiscussed? How has their popularity changed over time? Who have been the leading researchers? Answers to these questions areprovided by statistical analysis on keywords and by applying Latent Dirichlet Allocation to the titles and abstracts of the publications. The aim of this paper is to provide background information on the big picture of semantic analysis and its development over time.

AB - The first publications on sentiment analysis and opinion mining were published roughly a decade ago. Now it is time to lookback on the achievements so far. This paper presents statistics on the evolution of sentiment analysis. What kind of topics have beendiscussed? How has their popularity changed over time? Who have been the leading researchers? Answers to these questions areprovided by statistical analysis on keywords and by applying Latent Dirichlet Allocation to the titles and abstracts of the publications. The aim of this paper is to provide background information on the big picture of semantic analysis and its development over time.

KW - Latent Dirichlet Allocation

KW - Literature Study

KW - Sentiment Analysis

UR - https://www.scopus.com/pages/publications/85015199385

U2 - 10.1109/ICDMW.2016.0131

DO - 10.1109/ICDMW.2016.0131

M3 - Conference article in proceedings

SP - 890

EP - 899

BT - Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016

PB - IEEE

Y2 - 12 December 2016 through 15 December 2016

ER -

Research on Sentiment Analysis: The First Decade

Abstrakti

Conference

Pääsy asiakirjaan

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Sormenjälki

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