Sentiment Index of the Russian Speaking Facebook

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Introduction Social Sentiment Index Results Sentiment Index of the Russian Speaking Facebook International Conference on Computational Linguistics Dialogue 2014, Bekasovo, Russia Alexander Panchenko Digital Society Laboratory LLC, Moscow, Russia & Universite catholique de Louvain, Louvain-la-Neuve, Belgium June 8, 2014 Alexander Panchenko Sentiment Index of the Russian Speaking Facebook

description

A sentiment index measures the average emotional level in a corpus. We introduce four such indexes and use them to gauge average “positiveness” of a population during some period based on posts in a social network. This article for the first time presents a text-, rather than word-based sentiment index. Furthermore, this study presents the first large-scale study of the sentiment index of the Russian-speaking Facebook. Our results are consistent with the prior experiments for English language.

Transcript of Sentiment Index of the Russian Speaking Facebook

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Sentiment Index of theRussian Speaking Facebook

International Conference on Computational LinguisticsDialogue 2014, Bekasovo, Russia

Alexander Panchenko

Digital Society Laboratory LLC, Moscow, Russia &Universite catholique de Louvain, Louvain-la-Neuve, Belgium

June 8, 2014

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Motivation: Can we measure happiness?

Why such a wild idea as measuring happiness?

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Happiness: Google

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Happiness: semantic field

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Happiness: semantic field

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Happiness: self-reported vs estimated

self-reportedare you happy now?

estimated from socio-economical factorsgross national productquality of life, etc.

estimated from linguistic datapositive statements vs negative statementsseveral researchers considered this problem during last 10 yearsblogs: Mihalchea and Lui (2005), Mishne and Rijke (2006),Balog and Rijke (2006)social networks: Dodds et al. (2011), Kamvar and Harris(2011), Facebook Gross National Happiness index (FGNH) ofKramer (2010)

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Contributions

Two contributions of this paper to the exploration ofsentiment/happiness indexes are as follows:

We propose four indexes that gauge emotional level ofpopulation. Unlike most previous works, we not only deal withword-based indexes, but also device a text-based index.To the best of our knowledge, this is the first study ofsentiment index of the Russian-speaking social network.

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Facebook Corpus

Statistics of the Facebook corpus

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Facebook Corpus

Number of texts per day in the Facebook corpus

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Sentiment Detection Method

Most frequent positive and negative adjectives in theFacebook corpus

1500 emotional adjectives (600 negative, 900 positive)

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Sentiment Detection Method

Dictionary Sentiment Text Classification Approach

emotion delta ∆ ∈ [−1; 1] – direction and amplitude of textsentimentD+ – positive termsD− – negative termsw – wordt – textn – length of textα ∈ [0; 1] – a threshold

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Sentiment Detection Method

Comparison of Sentiment Classification Approaches

ROMIP 2012 – Sentiment Analysis Collection

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Social Sentiment Indexes

Sentiment Indexes

The goal of a sentiment index is to measure positiveness of socialnetwork users during some period.

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Social Sentiment Indexes

Sentiment Indexes

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Results of the social sentiment index calculation during theentire period

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Evolution of the word sentiment index sw during the entireperiod

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Word (sw) and text (st) sentiment indexes

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Positive and Negative Events

(1) 31-12-*—New Year (+);(2) 14-02-*—St.Valentine’s day (+);(3) 23-02-*—Man’s day (+);(4) 08-03-*—Woman’s day (+);(5) 09-05-*—Victory Day, World War 2 commemorative day (–);(6) 07-07-2012—Krasnodar Krai floods in Russia 6 (–);(7) 22-07-2012—A new unpopular law regulating non-profitorganizations in Russia 7 (–);(8) 16-09-2012—A mass protest against government in Russia 8 (–);(9) 25-10-2012—Hurricane Sandy in US (–).

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Word (ew) and text (et) emotional indexes

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Word and text emotional indexes

Word (ew ) and text (et) emotional indexes, compared to thenumber of words.

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Thank you! Questions?

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