<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="sommerdijk-etal-2016-tweets">
    <titleInfo>
        <title>Can Tweets Predict TV Ratings?</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Bridget</namePart>
        <namePart type="family">Sommerdijk</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Eric</namePart>
        <namePart type="family">Sanders</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Antal</namePart>
        <namePart type="family">van den Bosch</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-may</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)</title>
        </titleInfo>
        <originInfo>
            <publisher>European Language Resources Association (ELRA)</publisher>
            <place>
                <placeTerm type="text">Portorož, Slovenia</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We set out to investigate whether TV ratings and mentions of TV programmes on the Twitter social media platform are correlated. If such a correlation exists, Twitter may be used as an alternative source for estimating viewer popularity. Moreover, the Twitter-based rating estimates may be generated during the programme, or even before. We count the occurrences of programme-specific hashtags in an archive of Dutch tweets of eleven popular TV shows broadcast in the Netherlands in one season, and perform correlation tests. Overall we find a strong correlation of 0.82; the correlation remains strong, 0.79, if tweets are counted a half hour before broadcast time. However, the two most popular TV shows account for most of the positive effect; if we leave out the single and second most popular TV shows, the correlation drops to being moderate to weak. Also, within a TV show, correlations between ratings and tweet counts are mostly weak, while correlations between TV ratings of the previous and next shows are strong. In absence of information on previous shows, Twitter-based counts may be a viable alternative to classic estimation methods for TV ratings. Estimates are more reliable with more popular TV shows.</abstract>
    <identifier type="citekey">sommerdijk-etal-2016-tweets</identifier>
    <location>
        <url>https://aclanthology.org/L16-1473</url>
    </location>
    <part>
        <date>2016-may</date>
        <extent unit="page">
            <start>2965</start>
            <end>2970</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Can Tweets Predict TV Ratings?
%A Sommerdijk, Bridget
%A Sanders, Eric
%A van den Bosch, Antal
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 may
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F sommerdijk-etal-2016-tweets
%X We set out to investigate whether TV ratings and mentions of TV programmes on the Twitter social media platform are correlated. If such a correlation exists, Twitter may be used as an alternative source for estimating viewer popularity. Moreover, the Twitter-based rating estimates may be generated during the programme, or even before. We count the occurrences of programme-specific hashtags in an archive of Dutch tweets of eleven popular TV shows broadcast in the Netherlands in one season, and perform correlation tests. Overall we find a strong correlation of 0.82; the correlation remains strong, 0.79, if tweets are counted a half hour before broadcast time. However, the two most popular TV shows account for most of the positive effect; if we leave out the single and second most popular TV shows, the correlation drops to being moderate to weak. Also, within a TV show, correlations between ratings and tweet counts are mostly weak, while correlations between TV ratings of the previous and next shows are strong. In absence of information on previous shows, Twitter-based counts may be a viable alternative to classic estimation methods for TV ratings. Estimates are more reliable with more popular TV shows.
%U https://aclanthology.org/L16-1473
%P 2965-2970

Markdown (Informal)

[Can Tweets Predict TV Ratings?](https://aclanthology.org/L16-1473) (Sommerdijk et al., LREC 2016)

• Can Tweets Predict TV Ratings? (Sommerdijk et al., LREC 2016)

ACL

• Bridget Sommerdijk, Eric Sanders, and Antal van den Bosch. 2016. Can Tweets Predict TV Ratings?. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2965–2970, Portorož, Slovenia. European Language Resources Association (ELRA).