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                    <title type="main">News Information Decoupling: An Information Signature of Catastrophes in Legacy News Media</title>
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                <author>
                    <persName>
                        <surname>Nielbo</surname>
                        <forename>Kristoffer L.</forename>
                    </persName>
                    <affiliation>Center for Humanities Computing Aarhus, Jens Chr. Skous Vej 4, Building 1483, 3rd floor, DK-8000 Aarhus C, Denmark; DATALAB, School of Communication and Culture, Aarhus University, Helsingforsgade 14, DK-8200 Aarhus N, Denmark; Interacting Minds Centre, Jens Chr. Skous Vej 4, Building 1483, 3rd floor, DK-8000 Aarhus C, Denmark</affiliation>
                    <email>kln@cas.au.dk</email>
                </author>
                <author>
                    <persName>
                        <surname>Baglini</surname>
                        <forename>Rebekah B.</forename>
                    </persName>
                    <affiliation>Interacting Minds Centre, Jens Chr. Skous Vej 4, Building 1483, 3rd floor, DK-8000 Aarhus C, Denmark</affiliation>
                    <email>rbkh@cc.au.dk</email>
                </author>
                <author>
                    <persName>
                        <surname>Vahlstrup</surname>
                        <forename>Peter B.</forename>
                    </persName>
                    <affiliation>Center for Humanities Computing Aarhus, Jens Chr. Skous Vej 4, Building 1483, 3rd floor, DK-8000 Aarhus C, Denmark; DATALAB, School of Communication and Culture, Aarhus University, Helsingforsgade 14, DK-8200 Aarhus N, Denmark</affiliation>
                    <email>imvpbv@cc.au.dk</email>
                </author>
                <author>
                    <persName>
                        <surname>Enevoldsen</surname>
                        <forename>Kenneth C.</forename>
                    </persName>
                    <affiliation>Center for Humanities Computing Aarhus, Jens Chr. Skous Vej 4, Building 1483, 3rd floor, DK-8000 Aarhus C, Denmark</affiliation>
                    <email>kenneth.enevoldsen@cas.au.dk</email>
                </author>
                <author>
                    <persName>
                        <surname>Bechmann</surname>
                        <forename>Anja</forename>
                    </persName>
                    <affiliation>DATALAB, School of Communication and Culture, Aarhus University, Helsingforsgade 14, DK-8200 Aarhus N, Denmark</affiliation>
                    <email>anjabechmann@cc.au.dk</email>
                </author>
                <author>
                    <persName>
                        <surname>Roepstorff</surname>
                        <forename>Andreas</forename>
                    </persName>
                    <affiliation>Interacting Minds Centre, Jens Chr. Skous Vej 4, Building 1483, 3rd floor, DK-8000 Aarhus C, Denmark</affiliation>
                    <email>andreas.roepstorff@cas.au.dk</email>
                </author>
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                    <date>2021-06-07T08:11:58.638520823</date>
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                <publisher>Elisabeth Burr, University of Leipzig</publisher>
                <address>
                    <addrLine>Beethovenstr. 15</addrLine>
                    <addrLine>04107 Leipzig</addrLine>
                    <addrLine>Germany</addrLine>
                    <addrLine>Elisabeth Burr</addrLine>
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                    <term>Long paper</term>
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                <keywords scheme="ConfTool" n="keywords">
                    <term>Newspapers</term>
                    <term>Pandemic Response</term>
                    <term>Change Detection</term>
                    <term>Adaptive Filtering</term>
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                    <term>Programming</term>
                    <term>Content Analysis</term>
                    <term>Structural Analysis</term>
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            <div type="div1" rend="DH-Heading1">
                <head>Introduction</head>
                <p>As the first wave of Covid-19 virus spread across the world, content alignment of
                    news stories could be observed both within and between media sources. During
                    December 2019 and February 2020, Covid-19 news stories were, outside China,
                    interspersed with news coverage of other events (e.g., Hong Kong protests,
                    Iranian–American confrontation, Trump impeachment). As the virus spread across
                    Europe and America, news media front pages focused almost exclusively on the
                    pandemic, all news sections (politics, business, sports, and arts) related to
                    Covid-19, and breaking news became <hi rend="italic">corona news</hi> in
                    continuously updated media. From the perspective of cultural dynamics, the
                    Covid-19 pandemic provides a natural experiment that allows us to study the
                    effect of a global catastrophe on the dynamics of news media's information.
                    While news media are neither unbiased nor infallible as sources of events, they
                    do reflect preferences, values, and desires of a wide socio-cultural and
                    political user spectrum. As such, news media coverage of Covid-19 functions as a
                    proxy for how cultural information systems respond to unexpected and dangerous
                    events. </p>
                <p>Previous studies have shown that variation in newspapers' word usage is sensitive
                    to the dynamics of socio-cultural events (Guldi 2019 / Eijnatten et al. 2019 /
                    Daems et al. 2019), can detect event-driven shifts (Kestemont et al. 2014), and
                    accurately can model effects of change in comprehensive collections of
                    newspapers (Bos et al. 2016). Furthermore, the co-occurrence structure of
                    newspapers has been shown to accurately capture thematic development (Newman et
                    al 2006), and, when modelled dynamically, is indicative of the evolution of
                    cultural values and biases (Eijnatten et al. 2019 / Wevers 2019). Adaptive
                    smoothing and fractal analysis of word frequencies over time have been used to
                    identify distinct domains of newspaper content (e.g., advertisements vs.
                    articles) (Wevers et al. 2020) and to discriminate between different classes of
                    catastrophic events that display class-specific fractal signatures in, among
                    other things, word usage in newspapers (Gao et al. 2012). Several studies have
                    shown that measures of (relative) entropy can detect fundamental conceptual
                    differences between distinct periods (Guldi 2019), concurrent normative and
                    ideological movements (Barron et al. 2018), and even, development of ideational
                    factors (e.g., creative expression) in temporally dependent writings (Murdock et
                    al. 2015 / Nielbo et al. 2019a, 2019b). More specifically, a set of
                    methodologically related studies have applied windowed relative entropy to
                    thematic text representations to generate signals that capture information <hi
                        rend="italic">novelty</hi> as a reliable content difference from the past
                    and <hi rend="italic">resonance</hi> as the degree to which future information
                    conforms to said novelty (Barron et al. 2018 / Murdock et at. 2015). Two recent
                    studies have found that successful social media content shows a strong
                    association between novelty and resonance (Nielbo et al. 2021), and that
                    variation in the novelty-resonance association can predict significant change
                    points in historical data (Vranbæk et al. 2021). </p>
                <p>In this study we expand upon studies of novelty and resonance in cultural dynamics by modeling change in printed news media during the initial phase of Covid-19. Specifically, we propose the empirically derived principle of News Information Decoupling, which explains how the information flow in legacy media responds to catastrophic events.</p>
                  <figure>
                        <graphic url="Pictures/d4564e3c6f06cb745de32cdc08433b02.png"/>
                  </figure>
                    <p>Figure 1: 
                    <hi rend="color(#202122)">ℕ</hi>
                    <hi rend="color(#202122)">×</hi>
                    <hi rend="color(#202122)">ℝ</hi> slope baseline for four national newspapers that represents the left-right political spectrum. Data are sampled before Covid-19 phase 1 in Denmark initiated.
                </p>
                    <figure>
                        <graphic url="Pictures/6ebf90fe020e69c5e32871a1e8fb9033.png"/>
                    </figure>
                <p>Figure 2: Novelty (upper panel), resonance (middle panel), and event-defined 
                    <hi rend="color(#202122)">ℕ</hi>
                    <hi rend="color(#202122)">×</hi>
                    <hi rend="color(#202122)">ℝ</hi> slopes (lower panel) for center-left newspaper 
                    <hi rend="italic">Politiken</hi> before and during Covid-19 phase 1.</p>
                
            </div>
            <div type="div1" rend="DH-Heading1">
                <head>Results</head>
                <p>The reported results are based on a sample of fours national newspapers in
                    Denmark that collectively represent moderate-left ( <hi rend="italic"
                        >Politiken</hi>) and moderate-right ( <hi rend="italic">Berlingske</hi>),
                    and left ( <hi rend="italic">Information</hi>) and right-wing political
                    observation ( <hi rend="italic">Ekstrabladet</hi>). This paper focuses on
                    moderate newspapers during phase 1 of Covid-19, but all results have been
                    confirmed for the full political spectrum as well as all national newspapers in
                    Denmark (see Appendix for details on methods and data). </p>
                <p>To establish a baseline for novelty and resonance, we computed the pr. newspaper
                    linear slope for resonance on novelty ( <hi rend="color(#202122)">ℕ</hi>
                    <hi rend="color(#202122)">×</hi>
                    <hi rend="color(#202122)">ℝ</hi>) from December 01, 2019 to February 26, 2020
                    (the first case of Covid-19 in Denmark was registered on February 27, 2020). As
                    can be observed from Figure 1, the slopes are remarkably similar, indicating a
                    medium to strong association between novelty and resonance ( <hi rend="italic"
                        >M</hi>=0.56, <hi rend="italic">SD</hi>=0.06) before the national outbreak
                    of Covid-19. In the normal state of affairs, novelty and resonance therefore
                    seem to be coupled such that novel news items tend to resonate more than
                    overused and repetitive items and vice versa. This general news dynamic confirms
                    the intuition that news media, all things being equal, maintain their relevance
                    by propagating news. </p>
                    <figure>
                        <graphic url="Pictures/e4d8b16cdb7c0e68ced9a1d2f0b8777a.png"/>
                    </figure>
                <p>Figure 3: Novelty (upper panel), resonance (middle panel), and event-defined 
                    <hi rend="color(#202122)">ℕ</hi>
                    <hi rend="color(#202122)">×</hi>
                    <hi rend="color(#202122)">ℝ</hi> slopes (lower panel) for center-right newspaper 
                    <hi rend="italic">Berlingske</hi> before and during Covid-19 phase 1.</p>
                
                <p>The normal state of affairs was however severely disrupted by the rapid spread of Covid-19 and following lockdown on March 13. For 
                    <hi rend="italic">Politiken</hi> in Figure 2 it is apparent that between the first case (‘Virus’) and the ‘Lockdown’ there is a non-linear decrease in novelty (upper panel) which is countered by an inverted resonance response (middle panel). This initial decoupling of novelty and resonance does, in other words, coincide with the catastrophic Covid-19 event. While slightly less pronounced, the same decoupling patterns can be observed in 
                    <hi rend="italic">Berlingske</hi>, see Figure 3. In fact, decoupling of novelty and resonance can be observed in all national broadsheet newspapers irrespective of political observation and rare news phenomena where all news items are concerned with one event for an extended period of time (&gt;3 weeks).
                </p>
                <p>An interesting contrast that may be politically motivated can be observed around the phase 1 ‘Opening’ at April 15. While the center-left newspaper 
                    <hi rend="italic">Politiken</hi> was quite fast at re-establishing an almost normal state of affairs, the center-right 
                    <hi rend="italic">Berlingske</hi> showed a delayed linear novelty response for the remainder of the first phase. This is likely to reflect the level of support for the center-left government's decision making regarding lockdown and opening. The center-right newspaper seems to retain the decoupling for longer as they continue to focus on the economic and societal consequences of the government's Covid-19 policies.
                </p>
                <p>The <hi rend="color(#202122)">ℕ</hi>
                    <hi rend="color(#202122)">×</hi>
                    <hi rend="color(#202122)">ℝ</hi> computed on event-defined windows, e.g., ‘ <hi
                        rend="italic">Lockdown→Opening</hi>’, can be used for simple change
                    detection technique, see Figures 1 and 1 lower panels. As phase 1 unfolds, the
                    decoupling is observed as loss of association between novelty and resonance. In
                    the ‘ <hi rend="italic">Virus→Lockdown</hi>’ window (middle plot in lower
                    panel), the slope approaches zero (for <hi rend="italic">Politiken</hi> the
                    slope is actually negative), when the decoupling is most pronounced. The partial
                    return to normal can be observed in the (dis-)similarity between ‘ <hi
                        rend="italic">→</hi>
                    <hi rend="italic">Wuhan</hi>’ and ‘ <hi rend="italic">Opening→</hi>’ ( <hi
                        rend="italic">Politiken</hi>: 0.65→0.6, and <hi rend="italic"
                        >Berlingske</hi>: 0.48→0.36). </p>
            </div>
            <div type="div1" rend="DH-Heading1">
                <head>Concluding remarks</head>
                <p>In conclusion we propose the empirically-derived <hi rend="italic">News
                        Information Decoupling</hi> (NID) principle, which states that in response
                    to unexpected and dangerous temporally extended events, the ordinary information
                    dynamics of news media are (initially) decoupled such that the content novelty
                    decreases as media focus monotonically on the catastrophic event, but the
                    resonant property of said content increases as its continued relevance
                    propagates throughout the news information system. As such, NID behavior of the
                    news information flow is a signature of catastrophes. At the level of
                    methodology, this paper has illustrated how NID behavior of legacy media can be
                    identified using non-linear adaptive filtering and windowed linear fits for
                    resonance and novelty, and function provide input for change point detection
                    algorithms. </p>
                <p>There are multiple research paths that could contribute further to our understanding of NID. First, the predictive value of NID should be validated in terms of crisis management; second evaluation of NID's event scope is necessary, for instance, does NID only apply to a small set of negative events or does it generalize to a substantially larger set of significant events (e.g., moon landing, fall of the Berlin wall); third, comparisons of information micro-behavior as a function of newspaper values, for instance, left vs. right-wing newspapers or tabloid vs. broadsheet newspapers; and finally, multilingual validation of NID.</p>
            </div>
        </body>
        <back>
            <div type="div1" rend="DH-Heading1">
                <head>Methods</head>
                <div type="div2" rend="DH-Heading2">
                    <head>Data and normalization</head>
                    <p>The data set consists of all linguistic content from front pages of four
                        Danish national newspapers <hi rend="italic">Politiken</hi>, <hi
                            rend="italic">Berlingske</hi>, <hi rend="italic">Information</hi> and
                            <hi rend="italic">Ekstrabladet,</hi> sampled during December 1, 2019 to
                        June 1 2020. In order to normalize linguistic content, numerals and highly
                        frequent function words were removed, and the remaining data were lemmatized
                        and casefolded. Subsequently, the data were represented as a bag-of-words
                        (BoW) model using latent Dirichlet allocation in order to generate a dense
                        low-rank representation of each article. Novelty and resonance were
                        estimated for in windows of one week ( <hi rend="italic">w</hi> = 7). </p>
                </div>
                <div type="div2" rend="DH-Heading2">
                    <head>Novelty and resonance</head>
                    <p>Two related information signals were extracted from the temporally sorted BoW
                        model: <hi rend="italic">Novelty </hi>as an article <hi rend="italic">s</hi>
                        <hi rend="sup italic">(j)</hi>'s reliable difference from past articles <hi
                            rend="italic">s</hi>
                        <hi rend="sup italic">(j-1)</hi>
                        <hi rend="sub italic">, </hi>
                        <hi rend="italic">s</hi>
                        <hi rend="sup italic">(j-2)</hi>
                        <hi rend="italic">,…,s</hi>
                        <hi rend="sup italic">(j-w)</hi> in window <hi rend="italic">w</hi>: </p>
                    <figure>
                        <graphic url="Pictures/fbcdaa0cf52782752e74f6f5f20afff2.png"/>
                    </figure>
                    <p>and <hi rend="italic">resonance</hi> as the degree to which future articles
                            <hi rend="italic">s</hi>
                        <hi rend="sup italic">(j+1)</hi>
                        <hi rend="sub italic">, </hi>
                        <hi rend="italic">s</hi>
                        <hi rend="sup italic">(j+2)</hi>
                        <hi rend="italic">,…,s</hi>
                        <hi rend="sup italic">(j+w)</hi> conforms to article <hi rend="italic"
                            >s</hi>
                        <hi rend="sup italic">(j)</hi>: </p>
                    <figure>
                        <graphic url="Pictures/0e711d405ddd94c538f510a69904ac3c.png"/>
                    </figure>
                    <p>where <hi rend="color(#202122)">𝕋</hi> is the <hi rend="italic"
                            >transience</hi> of <hi rend="italic">s</hi>
                        <hi rend="sup italic">(j)</hi>: </p>
                    <figure>
                        <graphic url="Pictures/f4f296e39cfd8318bdd69db3d66354b0.png"/>
                    </figure>
                    <p>The novelty-resonance model was originally proposed in (Barron et al. 2018),
                        but here we propose a symmetrized and smooth version by using the
                        Jensen–Shannon divergence ( <hi rend="italic">JSD</hi>): </p>
                    <figure>
                        <graphic url="Pictures/90c715b0416b7787e6af33f66c41aa42.png"/>
                    </figure>
                    <p>with <hi rend="italic">M=1/2(</hi>
                        <hi rend="italic">s</hi>
                        <hi rend="sup italic">(j)</hi>
                        <hi rend="italic">+</hi>
                        <hi rend="italic">s</hi>
                        <hi rend="sup italic">(</hi>
                        <hi rend="sup italic">k</hi>
                        <hi rend="sup italic">)</hi>
                        <hi rend="italic">)</hi> and <hi rend="italic">D</hi> is the
                        Kullback-Leibler divergence: </p>
                    <figure>
                        <graphic url="Pictures/ad8a0d806a86d3ed128e0f1af746cd9a.png"/>
                    </figure>
                </div>
            </div>
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                </listBibl>
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