93545 - Communication Laboratory (Lm) (G.C)

Learning outcomes

The workshop aims to provide students with skills in the production of journalistic and media content (television, radio and internet). At the end of the course the student: - masters the main techniques of producing news and media content - is able to independently produce news content in written, oral or multimedia form

Course contents

WARNING. This course is about to change its title or training objectives. In the transitional phase, the title and training objectives for the 2021/2022 academic year remain, but it is essential to read the contents of the syllabus.
This laboratory is a natural continuation/extension of the course now called INFORMATION AND BIG DATA (LM) which, from the academic year 2022/23, introduces the hypotheses, methods and techniques used in the social sciences to analyse socio-political attitudes and behaviour with coded data (so-called quantitative analysis) taken both from surveys and from textual content freely expressed by users on social networks.
The laboratory may also be attended by those who have not attended the aforementioned course, provided that they are in some way familiar with its contents. To this end, in the first two lectures, these contents will be summarised and discussed between lecturer and participants.
The aim of the workshop is to introduce participants to the use of software and basic statistical techniques for conducting original analyses of survey data and textual data taken from social media in order to interpret "public opinion orientations" and test hypotheses regarding the factors influencing underlying individual attitudes.
To this end, students will be introduced to some advanced functions of Microsoft Excel and to the use of the statistical software STATA (freely available for Unibo students). The exercises will cover the implementation of monovariate (simple tables), bivariate (tables of two cross variables), and multivariate (linear and logistic regression models) analyses, text classification (Linear Discriminant Analysis) and interpretation of results.
These techniques will be used with comparative survey data (European Social Survey, World Value Survey) and with data from social media in Italian and/or English. The objective will be to carry out empirical analyses 'on their own', by directly examining the data, regarding the topics covered in the first module: the way in which individuals position themselves along the fractures and divisive issues salient today (statism/liberalism, globalism/nationalism, climate change, immigration, civil rights); the factors influencing the formation of these opinions and voting choices (ascribed characteristics, position in the social structure, long-term political predispositions, evaluation of incumbent governments and leaders).
During the final laboratory lectures, participants are expected to present their own elaborations on one of these topics.

Readings/Bibliography

Stockemer, Daniel, G. Stockemer, and Glaeser. 2019. 50 Quantitative Methods for the Social Sciences. Springer.

Bethlehem, Jelke. 2017. Understanding Public Opinion Polls. Chapman and Hall/CRC. Individual chapters specified in class by the lecturer.

Brooker, R. G., and T. Schaefer. 2015. “Public Opinion in the 21st Century. Methods of Measuring Public Opinion.” Unpublished Work). Available online: http://www. uky. edu/AS/PoliSci/Peffley/pdf/473Measuring% 20Public% 20Opinion. pdf (accessed on 5 December 2018).

Hillygus, D. Sunshine. 2015. “The Practice of Survey Research: Changes and Challenges.” In New Directions in Public Opinion, Routledge, 56–75.

“Linear vs Logistic Regression: A Succinct Explanation.” KDnuggets. https://www.kdnuggets.com/linear-vs-logistic-regression-a-succinct-explanation.html/ (July 10, 2022).

“Stata Learning Modules.” https://stats.oarc.ucla.edu/stata/modules/ (July 10, 2022).

“Stata Web Books Logistic Regression with Stata.” https://stats.oarc.ucla.edu/stata/webbooks/logistic/ (July 10, 2022).

“Stata Web Books Regression with Stata.” https://stats.oarc.ucla.edu/stata/webbooks/reg/ (July 10, 2022).

Teaching methods

The course consists of fifteen working sessions in which students will be invited to actively participate. The first three sessions will consist of classic lectures recapitulating the essential contents of research methodology and public opinion analysis. The bulk of the sessions will consist of exercises in which participants will be introduced to the use of the main statistical techniques, using STATA software, on comparative survey data (European Social Survey, World Value Survey). Participants will also be required to take turns in presenting their work in preparation for the final paper. All lectures will be held in presence. It is necessary for each participant to have their own personal computer connected to the Internet on which an up-to-date version of Stata must be installed (instructions on how to install Stata will be given during the lessons).

Attendance is compulsory. No more than four sessions may be missed. To facilitate individual study and practice with statistical techniques, video recordings of some lectures will be made available to participants.

Assessment methods

Each student will have to write a paper (of approximately 15,000 characters) on one of the topics covered in the course, basing his or her analysis on the scientific literature and on original elaborations of data from one of the surveys that will be provided by the lecturer and presented in class, or on quantitative analyses of textual data taken from social networks. Students who are found to have committed plagiarism - that is, if it appears that parts of the paper have been transcribed from other documents of any kind - will be excluded from the course and will not be admitted to the examination. The final grade will be based on the evaluation of the paper and its discussion as well as an oral interview covering all course content as usual. The paper may be a development of the one presented and discussed for the course now entitled "INFORMATION AND BIG DATA", supplemented with relevant original empirical analyses.

Teaching tools

Projector, PC, Unibo licence for STATA statistical software, classroom equipped with power sockets and wireless internet connection, cloud sharing of course materials (presentations, datasets, syntax files).

Office hours

See the website of Salvatore Vassallo