conceptualizing and measuring news exposure as network of users and news items

Conceptualizing and measuring news exposure asnetwork of users and news items

Damian Trilling

University of AmsterdamDepartment of Communication Science

Amsterdam School of Communication [email protected]

DGPUK FG Methoden23-09-2016

1 Common assumptions. . . and why they are wrong

2 Toward new theories of news flows

3 News exposure as network of users and news itemsA modelImplementation

4 Conclusion

Common assumptions

Common assumptions Toward new theories of news flows Network of users and news items Conclusion

Common assumptions

We do as if these assumptions would still hold . . .(have they ever?)

“People use a fixed set of newsoutlets”

“People can name these outlets”“People use these outlets with aconstant frequency”“The content of the outlets isstatic”

Conceptualizing and measuring news exposure as network of users and news items Damian Trilling


Common assumptions


“People use a fixed set of newsoutlets”

“People can name these outlets”

“People use these outlets with aconstant frequency”“The content of the outlets isstatic”



Common assumptions


“People use a fixed set of newsoutlets”“People can name these outlets”

“People use these outlets with aconstant frequency”

“The content of the outlets isstatic”



Common assumptions


“People use a fixed set of newsoutlets”“People can name these outlets”“People use these outlets with aconstant frequency”

“The content of the outlets isstatic”



Common assumptions


“If we know content of the outletand frequency of use, we can inferto which content people areexposed”

“Outlets are a meaningful categoryto categorize distinct content”“Content produced by one outlet isdelivered via one channel”



Common assumptions


“If we know content of the outletand frequency of use, we can inferto which content people areexposed”

“Outlets are a meaningful categoryto categorize distinct content”

“Content produced by one outlet isdelivered via one channel”



Common assumptions


“If we know content of the outletand frequency of use, we can inferto which content people areexposed”“Outlets are a meaningful categoryto categorize distinct content”

“Content produced by one outlet isdelivered via one channel”



. . . and why they are wrong

But they are wrong.

• News providers spread their content via different channels:website, apps, social media, . . .

• Large share (typically 33%–50%) of website traffic comes vialinks on social media

• tailored, personalized, targeted content


Toward new theories of news flows


Toward new theories of news flows

Transmission of societally relevant information

• before: few distinct channels, largely the same for everyone• now: also social network sites, personalized media, . . .• complicating factor: citizens influence the news diffusionprocess by sharing articles (feedback loops)

⇒ news products get unbundled



Unbundling of news

• single news item instead of collection of items bundled in, e.g.a newspaper

examples

• aggregators (Google News)• pay-per-article (Blendle)



This renders questions like “Did you watch the news yesterday?”pointless and makes it necessary to shift perspectives towards theindividual news item.

solid-state entity of news has become liquid.

(see also Bauman, 2007).



Consequences of liquid news

Revisting theories• distinction between mass communication and (mediated)personal communication cannot be upheld Perloff2015

• the question “who sets the media agenda?” has become “illstructured” Russell Neuman e.a., 2014, because traditional and socialmedia interact and resonate Deuze, 2008

Re-integrating old theories• Two-step-flow• apply news value theory to news sharing



Thorson & Wells: Curated news flows

• tracking data from Facebook app• combined with survey data

⇒ one example of how to tackle mesaurement of liquid news: Howcan we measure who has been exposed to which news item?Thorson, K., & Wells, C. (2016). Curated flows: A framework for mapping media exposure in the digitalage. Communication Theory, 26, 309–328. doi:10.1111/comt.12087


News exposure as network of users and news itemsA model


A model

Basics

A network approach• nodes of different types• edges of different types



A model

Conceptualization

Nodes

• news item: node with a number of properties:• timestamp• news values• medium• topic• . . .

• user: node with a number of properties• age• gender• . . .



A model

Conceptualization

Edges

• news item ↔ news item• is_similar

• user → news item• has_read

Other conceptualizations possible, e.g. taking into accounttimestamps to explicitly model chains of link sharing)



A model

News exposure as network of users and news items


is (

near

ly)

iden

tica

l

News item 5

News item 4

News item 3

News item 2

topic = economy

source = ANP

date = 06-12-2015

frames = [human interest, conflict]

reads

reads

A

B

C

reads

reads

... ... ...

medium = nu.nl

medium = nrc.nl

age = 59

gender = M

age = 27

gender =F

News item 1 age = 59

gender = M

... ... ...readsis (nearly) identical


A model

Advantages

• It allows to predict which item a given person is exposed to –irrespective of the channel.

• However, if one is interested in the channel instead, one couldalso predict the channel.

• If the news items are time-stamped, one can also investigatehow information spreads in the news environment.



Implementation

Implementation

Data collection

• Collect info about user nodes with surveys• Use tracking for news nodes (user-news-edges)

Enriching the dataset

• cosine similarity, Levenshtein distance to determine (nearly)intical article

• automated content analysis to determine properties of articles


Again, different conceptualizations would be possible

• outlets as additional nodes• directed edges for news flows (“originates_from”)• . . .


Implementation

Storing, accessing, and analyzing the data

• graph database• specific, derived datasets for each RQ at hand• e.g., collapsing nearly-identical articles, aggregating, . . .



Conclusion

• “outlet” becomes less and less a meaningful category• unbundling of news items• measure exposure to specific items• conceptualize (and store, analyze) as network of users anditems



Linking this to what we heard yesterday

• intentional vs non-intentional use: surveys are bad inmeasuring the latter

• Harsh’s conceptualization of overlap: outlets as nodes, doubleusage as edge weight

• avoids problems of site-centric measurements (Claes’ & Peter’spresentation and paper)

• and of course, this is one thing that I’ll do with the trackingdata Judith talked about



Questions?

[email protected]@damian0604

www.damiantrilling.net

www.personalised-communication.net


conceptualizing and measuring news exposure as network of users and news items

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