02/05/2023 OECD Ghent Sept 2016 1

‘Science Culture’ Indicators from Media Monitoring

Ahmet Suerdem (Bilgi, Istanbul)Martin W Bauer (LSE)

ahmet.suerdem@bilgi.edu.tr

02/05/2023 OECD Ghent Sept 2016 2

Fish tanks and their ambience

02/05/2023 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

Specific topics

UK

TR

Disciplines [OECD]

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 construction2. Cultural indicators (Gerber, 1969)

1. Media attention2. Saliency3. 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 Indicators1. 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 prospectsnew technique offers the prospect of GM crops tailor-made for specific situationsBASF 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)

2014