Suerdem - Science culture indicators from media monitoring

‘Science Culture’ Indicators
from Media Monitoring
Ahmet Suerdem (Bilgi, Istanbul)
Martin W Bauer (LSE)
ahmet.suerdem@bilgi.edu.tr
28/09/2016 OECD Ghent Sept 2016 1

28/09/2016 OECD Ghent Sept 2016 2
Fish tanks and their ambience

28/09/2016 OECD Ghent Sept 2016 3
Science is global, ‘science culture’ remains local
Science culture = a matter of mentality

Background and project MACAS (mapping the
cultural authority of science)
• Mass media: cultivation functions on public
opinion -> cultural repository for
understanding how public understand science.
• Trends in public opinion: surveys and polls
• Automatized media monitoring short, regular
intervals without extra costs.
• MACAS project aims to produce science culture
indicators through automatic content analysis
of digital news

Three project news corpora
1. MACAS media monitoring project [UK-
Germany-India 1990-2013]:
• Times –Mirror(UK)
• Spiegel-Suddeutsche (Germany)
• Times of India
2. Tubitak SMM project in Turkey [1999-2015]
• Hurriyet
3. ‘Beyond’ UK news corpus [2000-2016]:
biotechnology case study: attention,
salience, sentiment, structure

Intensity of science news
UK GERMANY

Beyond MACAS: Need for an open access Science in
the Media Monitoring system:
• Early detection of adverse events: feed-back
for the policy makers, science
communicators and citizens
• Artificial intelligence technologies: to
construct indicators to monitor public
attitudes towards science and technology
through media data.

Methodological steps:
1. Crawling the web for corpus construction
2. Cultural indicators (Gerber, 1969)
1. Media attention
2. Saliency
3. Sentiment analysis
4. Structure

1. Corpus construction: Issues In Automatic
crawling:
• Web as a corpus “surrogate”: low level of
control on data.
• Massive document collections on a wide
range of topics representing different
jargons.
• Not just automatizing the keyword search:
an intelligent and actionable corpus
construction strategy is needed

Biotechnology corpus
Selection of the newspapers:
popular or quality press; left or conservative worldviews; leader or
follower, high or low readerships.
Opinion leaders with high readership (Telegraph (quality) and Daily
Mail (popular).
Selecting the news: Determining the keywords is a challenging
task as these are not only grammatical categories but also social
categories representing the thematic focus of the study.
Ontological approach:
We have organized the ontology into the following core conceptual
facets: Generic (i.e. genome), organisms (i.e. enviropig), applications
(i.e. cloning), and peripheral facets related disciplines
(i.e biomedicine), biology (i.e. genetics), tools (ie Bioreactor),
companies (Celera), and organizations (i.e. OECD).

Cultural Indicators
1. Media attention:.
Words: existential problems such as regenerative medicine and aging
Bigrams: “decoding the mystery of life”
Named entities: private or public biotechnology research

Regenerative medicine
the creation of stem cells by therapeutic cloning
based on human embryonic stem cells .
develop new sources of parent stem cells , to treat serious diseases
therapeutically useful human stem cells
be cloned for research on the use of stem cells for therapies.
huge potential of embryonic stem cells to alleviate suffering.
Economic prospects
new technique offers the prospect of GM crops tailor-made for specific situations
BASF included the nptII gene in their GM potato. The gene will help protect
the science shows overwhelmingly that GM crops will help to ease world hunger
before concluding that GM crops would not benefit the Third World
however , that GM technology will lead to more efficien
has urged government to embrace GM food as the only way to feed the
Concordances: how stem cells and GM are represented in the text

2. Emphasis: Density of biotechnology topic between 2000-2015
GM debate, Dolly
Stem cells from
mouse embryos

telegraph dailymail
Saliency of biotechnology compared to all news in different newspapers

3. Tendency: “Fashion cycle” ?

regenerative medicine (stem, cell, research, patient, human, body, heart,
blood, tissue, disease);
gene therapy (gene, therapy, genetic, disease, immune, patient,
treatment, virus, );
stem cell controversy (stem, cell, research, scientist, human, embryo, egg,
genetic disease, treatment);
human genome research (human, genome, research, scientist, gene,
sequence, genetic, DNA, code, life);
commercial biotechnology (drug, companies, market, fund,
biotechnology, science, research, medical, treatment, world)
GM controversy (GM, food, crops, plant, agriculture, product, research,
technology, animals, gene).
4. Structure: LDA TOPIC DETECTION

Change in intensity of biotechnology topics (2000-2015)

Suerdem - Science culture indicators from media monitoring

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