1 New Media Literacy For Media Professionals Andrej Školkay Leonardo da Vinci Project 2012-2014: New Media Literacy for Media Professionals Partners: SKAMBA

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New Media LiteracyNew Media LiteracyFor Media ProfessionalsFor Media Professionals

Andrej Školkay Andrej Školkay

Leonardo da Vinci Project 2012-2014:New Media Literacy for Media ProfessionalsPartners: SKAMBA (SK), Media21Foundation

(BG), FOPSIM (MT) and Videovest (RO).This presentation was prepared by SKAMBA and is free to

use under condition of acknowledging autorship

The key project objective:

To help journalists, especially freelancers, in search for information

and in data analysis with freely available software

+some update on recent developments

in online issues (e.g. ethics)

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The key long-term aim:to contribute to improved quality of media

and communication in EPS via strengthening skills and

exchange of experienceand best practices of professionals in media

and communication.

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+

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Analog vs. digital information

1950 1960 1990 2010

Włodzimierz Gogołek, [email protected] Institute of Journalism, University of Warsaw, Refining Information from the Internet. The New Information Source for Media

For the first time the sum of digital information produced during one year (2010) exceeded a Zetta Byte

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Włodzimierz Gogołek, [email protected] Institute of Journalism, University of Warsaw, Refining Information from the Internet. The New Information Source for Medi

Evolution of Communication/Media

access

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to obtain previously unavailable information about: social phenomena,

countries, organizations and individuals (such as their mutual relations, migrations,

etc.).




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Advanced tools

• Attentio DigPop

• Radian6 Sysomos

• NetBase Collective Intellect

Alterian Google Alerts

Google Books Ngram Viewer

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76% accuracy

e.g. Geocoding




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Semantic Search - Getshighest amount valid content

Boolean SearchMisses 40%

Keyword OnlyOverstated 800%

SEARCH TECHNOLOGY COMPARISONS




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There is a paradox related to forecasting in many areas within the social sciences; methods of pattern recognition and statistical prediction

are more difficult to apply in the short term than they are in the long

term.




Do we live in less or more

war-orientated world in the last 20 years?




In the 1993 Foreign Affairs article, Huntington writes:

It is my hypothesis that the fundamental source of conflict in this new world will not be primarily ideological or primarily economic.

The great divisions among humankind and the dominating source of conflict will be cultural. Nation states will remain the most

powerful actors in world affairs, but the principal conflicts of global politics will occur between nations and groups of different

civilizations. The clash of civilizations will dominate global politics. The fault lines between civilizations will be the battle lines of the

future.[2]

In the end of the article, he writes:This is not to advocate the desirability of conflicts between civilizations. It is to set forth

descriptive hypothesis as to what the future may be like




http://en.wikipedia.org/wiki/The_Clash_of_Civilizations#cite_note-FAarticle-2




BUT!

Interpretation!




World Peace, 1800-2000, English books




Peace, 1800-2000, English books

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http://emm.newsbrief.eu/NewsBrief/clusteredition/sk/latest.html




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http://emm.newsexplorer.eu/NewsExplorer/home/en/latest.html




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http://medisys.newsbrief.eu/medisys/homeedition/en/home.html




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http://emm-labs.jrc.it/




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http://emm-labs.jrc.it/

EXAMPLES: Geo Real Time Categories example Swine Flu - real time monitoring of swine flu reports in the news using Google maps Or on Google Earth

Geo real time clusters - real time visualization of news clusters Google Maps Or on Google Earth




http://press.jrc.it/geo?type=rss&format=html&language=all&category=SwineFlu

http://press.jrc.it/geo?type=rss&format=ref&language=all&category=SwineFlu

http://press.jrc.it/geo?type=cluster&format=ref&language=all

What can we achieve?

How do we achieve that?

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Pedro Pinto´s algorithm

Rooting out rumors, epidemics,

and crime




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an algorithm that can identify the source of an epidemic or

information circulating within a network




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E.g. Finding the source of a Facebook rumor

Identifying the brains behind a terrorist attack




The assessment of emotional relationships

• sympathy,

• resentment,

• sense of happiness,

• optimism,

• pessimism,

• fear, anxiety. 30

John Hersey, The New York Times Company, September 9, 2012

http://www.nytco.com/

http://www.nytco.com/

TRACKING THE FLU

The relative frequency of flu-related keywords in Google searches closely tracks flu statistics in Poland as monitored by the government officials

Information on the course of the 2010 presidential elections in Poland

The negative conotation of the social media contents about the leading candidates, broken down by weeks (5 May - 4 July 2010) - the number of references

HOW It is Possible

To Locate a Terrorist?




Global geocoded tone of all Summary of World Broadcasts content, January 1979–April 2011

mentioning “Bin Laden”

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Illustrative Risk Map based on World Bank, UN, and Bureau of Statistics Data.

Illustrative Risk Map based on World Bank, UN, and Bureau of Statistics Data.

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Documents

1 New Media Literacy For Media Professionals Andrej Školkay Leonardo da Vinci Project 2012-2014: New Media Literacy for Media Professionals Partners: SKAMBA