By analyzing social and linguistic dynamics in big corpora, we want to understand how to build consensus and promote spreading of information within a given context.

1. Marco Guerini
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2. INTRODUCTION
CONSENSUS AND SPREADING
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3. Premise
Information is vital, it creates emotions,
moves ideas, brings people to act.
By analyzing social and linguistic dynamics,
we want to understand how to build
consensus and promote spreading of
information within a given context.
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4. Premise
By means of a series of examples, I will
show some of the characteristics that
linguistic communication must have to be
effective.
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5. Approach
• Automatic analysis and recognition of the
persuasive impact of communication.
• Address the various effects which
persuasive communication can have in
different contexts on different audiences.
• Focus on the analysis of big corpora
specifically developed for the task.
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6. Persuasive Corpora
• Corpus, -digital- collection of texts from a
specific author, on a given topic, of a given
type.
• Linguistic data should be possibly
augmented with annotation of various
audience reactions and metadata.
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7. 2 Examples of Corpora
• CONSENSUS - Political speeches tagged
with audience reactions.
• SPREADING - Post on Social Networks
annotated with I_like, comments, etc.
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8. Consensus Indicators
• Positive-Focus: a persuasive attempt that sets a
positive focus in the audience. Tags considered:
{APPLAUSE} , {STANDING-OVATION} ,
{SUSTAINED-APPLAUSE} , {CHEERING} , etc.
• Negative-Focus: a persuasive attempt that sets a
negative focus in the audience. Negative focus set
towards the object of the speech not on the speaker.
{BOOING} , {AUDIENCE} No! {/AUDIENCE}
• Ironical: Indicate the use of ironical devices in
persuasion. Tags considered:
{LAUGHTER} and multiple tags containing laughter.
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9. Freedom has many difficulties and democracy is not
perfect. But we have never had to put a wall up to keep
our people in, to prevent them from leaving us.
{APPLAUSE ; CHEERS}
I want to say on behalf of my countrymen who live
many miles away on the other side of the Atlantic, who
are far distant from you, that they take the greatest
pride, that they have been able to share with you, even
from a distance, the story of the last 18 years. I know of
no town, no city, that has been besieged for 18 years
that still lives with the vitality and the force, and the
hope, and the determination of the city of West Berlin.
{APPLAUSE ; CHEERS}
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10. Spreading Indicators
White buzz positive comments. “The best product I have
ever bought”
Black buzz negative comments. “Do not buy this product, it
is a rip-off”
Raising discussion the ability to induce discussion among
users
Controversiality polarize the audience (pro or against the
given content)
Fostering Elaboration induce to elaborate on the given
content
…

11. Post Text Like ReShare Comments
Consensus is about the subtle art of 1218 54 360
saying the right thing at the right moment.
Consensus is about the art of knowing 2 0 5
what to say.
… … … …
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12. Methodology
• Classical approaches based on the study
of text characteristics. Simple count of
key-words in the document or analysis of
its linguistic structures.
• By means of specific mathematical
formulae we can define the persuasive
impact of linguistic material (words or
structures that get a lot of applauses,
reshare, etc.)
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13. Text Characteristics
Words used
Topics
Linguistic Style
Readability Difficulty
Rhetorical Structure
…

14. THE BIG PICTURE
CONSENSUS AND SPREADING
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15. 5 Elements
WHEN
WHO WHAT
WHERE HOW
Who delivers the content. What the content “says”. How
it is said. When it was delivered. Where it was delivered.
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16. An Example
How is it possible that this video
hit 1 billion views - in only five
months - on YouTube???
If you want check:
GANGNAM STYLE
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17. Consensus
The new internet earworm.
Absolutely terrific!
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18. Spreading
The new internet earworm.
Absolutely terrific!
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19. WHO
DELIVERS THE MESSAGE?
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20. The new internet
earworm. Absolutely
terrific!
Hey guys, check this out!
We’ve been dancing all
night at the White House!
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21. Standard Approaches
• Based on the study of WHO.
• “Easy” to model by means of graphs
where nodes represent users.
• Some nodes have interesting properties.
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22. Standard Approaches
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23. Standard Approaches
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24. Language and Role
• Opinion leaders have a particular
language style that characterize them.
We can identify those who can
potentially draw a crowd, within a group,
by analysing their language.
[Quercia et al. “In the mood for being influential on Twitter”]
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25. Language and Gender
Female’s rhetoric far less aggressive than
male’s - negative-focus tags density 60
times higher.
70%
60%
Carefully choose who shall 50%
deliver the communication 40%
according to context. 30%
20%
10%
[Guerini et al. “The New Release of CORPS”] 0%
Male
Female
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26. WHEN
IS IT BETTER TO DELIVER THE MESSAGE?
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27. Time
• Best time for posting on Twitter: from 9
a.m. to 13 p.m.
• Higher CTR: mid morning and early
afternoon
• Higher reshare: late afternoon
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28. Time
Morning. Reads Evening. In-depth analysis
35
30
25
20
15
10
5
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
It is better to deliver a content when users are
highly receptive. Pay attention to the effect you
want to achieve (only reads or in-depth analysis).
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29. Language and Events
Events that split the timeline in a before and after can
be relevant for persuasive language.
The word “war” used 5 times more by G. W. Bush after
9/11. But, while before 9/11 it was widely used to get
applauses, after it never got an applause. Freq
Persuas
Specific events can lead a good
communicator to change, not
as much his/her words, rather Freq
their rhetorical/persuasive use. Persuas
Before After
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30. WHAT
DOES THE CONTENT SAY?
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31. High Level Characteristics
Today I’m very happy. Even if I have few days off, the sea and
landscapes are stunning. Hiking away from the damned
Text only
work…
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32. High Level Characteristics
Today I’m very happy. Even if I have few days off, the sea and
landscapes are stunning. Hiking away from the damned Text + Pic
work…
Trivially: more
effective
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33. This holds true for a post, but also for an e-
mail, a presentation, etc. Graphical and
pictorial information grab users’ attention.
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34. HOW
TO SAY IT?
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35. Affective Words
Today I’m very happy. Even if I have few days off, the sea
and landscapes are stunning. Hiking away from the
damned work…
Usually a text with an
affective load spreads more.
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36. Affective Language
Positive language is more viral than negative
one (anger and fear are viral, but not sadness).
What really matters is affective arousal (joy,
anger and fear have high arousal, while
sadness has a low arousal).
How to convey negative news
without getting others down?
[Berger and Milkman “Social Transmission, Emotion, and the Virality of Online Content”]
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37. Readability and Difficulty
Thus "phenomenology" means -- to let that which shows itself
be seen from itself in the very way in which it shows itself
from itself.
(Martin Heidegger, Being and Time)
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38. Text difficulty - Example
Scientific articles and readability. Only
content should matter, nonetheless:
• Bookmarked+  harder to read - Fogg-index = 21.1
• Downloaded+  easier to read - Fogg-index = 18.2
A text that is easy to read brings about
an immediate action, a text hard to read
induces people to procrastinate…
[Guerini et al. “Do Linguistic Style and Readability of Scientific Abstracts Affect their Virality?”]
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39. Coarse Language
Today I’m very happy. Even if have few days off, the sea and
Che figata, il mare é stupendoI e i paesaggi commoventi. Solo un
landscapes are stunning… BTW
imbecille tornerebbe al lavoro. work sucks!!
Using vulgar expression does not
necessarily bring about negative
reactions...
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40. Coarse Language and Consensus
• Surprisingly, coarse language used in posts with
lots of comments or likes (coverage 1.2), but not
in controversial posts (coverage 0.9).
You can actually use coarse language
to obtain positive reactions…
[Strapparava et al. “Persuasive Language and Virality in Social Networks”]
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41. Irony and Simple Language
• Reagan - aka the “great communicator” -
used irony (laughter density three times
higher as compared to other speakers)
• Reagan used a simple language: his
persuasive words (and only those)
polisemy degree is double.
Irony and simple language can be
used as an instrument for consensus.
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42. Conclusions
• To understand how content can catalyze
consensus and spread, we need to study
the who, what and how.
• Focus on the analysis of big corpora
specifically developed for the task.
• A series of examples revealed specific
characteristics of effective linguistic
communication.
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43. References
• Berger J.A. and Milkman K.L. (2009) Social Transmission, Emotion, and
the Virality of Online Content. Social Science Research Network Working
Paper Series.
• Guerini M., Strapparava C. and Ozbal G. (2011) Exploring text virality in
social networks. In Proc. of ICWSM-11.
• Guerini M., Pepe A. and Lepri B. (2012) Do linguistic style and
readability of scientific abstracts affect their virality? Proceedings of
ICWSM-12.
• Guerini M., Strapparava C. and Stock O. (2008) CORPS: A Corpus of
Tagged Political Speeches for Persuasive Communication Processing.
Journal of Information Technology & Politics, 5(1):19-32.
• Guerini M., Giampiccolo D., Moretti G., Sprugnoli R. and Strapparava C.
The New Release of CORPS: a Corpus of Political Speeches Annotated
with Audience Reaction. Forthcoming.
• Quercia D., Ellis J., Capra L. and Crowcroft J. (2011) In the mood for
being influential on twitter. Proceedings of IEEE SocialCom-11.
• Strapparava C., Guerini M. and Ozbal G. (2011) Persuasive language and
virality in social networks. Affective Computing and Intelligent Interaction,
357-366.
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44. THANKS!
marco.guerini@trentorise.eu
www.marcoguerini.eu
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