Sentiment analysis using automatically labelled financial news

Michel Généreux; Thierry Poibeau; M. Koppel

Sentiment analysis using automatically labelled financial news

Michel Généreux
, Thierry Poibeau
, M. Koppel

Department of Computer Science and Artificial Intelligence

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Given a corpus of financial news labelled according to the market reaction following their publication, we investigate cotemporeneous and forward-looking price stock movements. Our approach is to provide a pool of relevant textual features to a machine learning algorithm to detect substantial stock price variations. Our two working hypotheses are that the market reaction to a news is a good indicator for labelling financial news, and that a machine learning algorithm can be trained on those news to build models detecting price movement effectively.

Original language	American English
Title of host publication	LREC 2008 Workshop on Sentiment Analysis: Emotion, Metaphor, Ontology and Terminology
State	Published - 2008

Bibliographical note

Place of conference:Morocco

Cite this

@inproceedings{73a8b8708c6c4c87a79a56f9469c5eaa,

title = "Sentiment analysis using automatically labelled financial news",

abstract = "Given a corpus of financial news labelled according to the market reaction following their publication, we investigate cotemporeneous and forward-looking price stock movements. Our approach is to provide a pool of relevant textual features to a machine learning algorithm to detect substantial stock price variations. Our two working hypotheses are that the market reaction to a news is a good indicator for labelling financial news, and that a machine learning algorithm can be trained on those news to build models detecting price movement effectively.",

author = "Michel G{\'e}n{\'e}reux and Thierry Poibeau and M. Koppel",

note = "Place of conference:Morocco",

year = "2008",

language = "American English",

booktitle = "LREC 2008 Workshop on Sentiment Analysis: Emotion, Metaphor, Ontology and Terminology",

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T1 - Sentiment analysis using automatically labelled financial news

AU - Généreux, Michel

AU - Poibeau, Thierry

AU - Koppel, M.

N1 - Place of conference:Morocco

PY - 2008

Y1 - 2008

N2 - Given a corpus of financial news labelled according to the market reaction following their publication, we investigate cotemporeneous and forward-looking price stock movements. Our approach is to provide a pool of relevant textual features to a machine learning algorithm to detect substantial stock price variations. Our two working hypotheses are that the market reaction to a news is a good indicator for labelling financial news, and that a machine learning algorithm can be trained on those news to build models detecting price movement effectively.

AB - Given a corpus of financial news labelled according to the market reaction following their publication, we investigate cotemporeneous and forward-looking price stock movements. Our approach is to provide a pool of relevant textual features to a machine learning algorithm to detect substantial stock price variations. Our two working hypotheses are that the market reaction to a news is a good indicator for labelling financial news, and that a machine learning algorithm can be trained on those news to build models detecting price movement effectively.

UR - https://scholar.google.co.il/scholar?q=Sentiment+analysis+using+automatically+labeled+financial+news&btnG=&hl=en&as_sdt=0%2C5

M3 - Conference contribution

BT - LREC 2008 Workshop on Sentiment Analysis: Emotion, Metaphor, Ontology and Terminology

ER -

Sentiment analysis using automatically labelled financial news

Abstract

Bibliographical note

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