These videos are part of the Emory College Language Center Speaker Series. Previous events are archived on our website under "Events".
What can we learn about the world (and the media system) by analyzing millions of news articles or tweets? Media content analysis has historically been the domain of the social sciences, but recently we are witnessing a strong trend towards the automation of many tasks, paving the way for a new – computational – approach to social science and the humanities. In this talk, I will survey the results obtained over the past 5 years at the Intelligent Systems Laboratory of Bristol, in the area of automating the analysis of news media content. By combining techniques from machine translation, pattern recognition, statistical learning, information retrieval, I will analyze patterns connected to the past US Presidential Elections, to UK public opinion, and to EU cultural biases.
The talk illustrates a quantitative social science approach to texts developed by the author, Quantitative Narrative Analysis (QNA). QNA relies on computer-assisted story grammars to analyze narrative, where a story grammar is the simple Subject-Verb-Object (SVO) structure. In narrative, Subjects are typically social actors – individuals, groups, organizations – Verbs are actions, and Objects are both social actors and physical and abstract objects. To each of the three SVO components one can add several attributes to capture the complexity of stories (e.g., name of an individual, number of actors in a group, time and space of action). The talk will illustrate the power of the approach using data collected by the author from newspapers on the rise of Italian fascism (1919–1922) (300,000 SVOs) and Georgia lynchings (1875–1930) (7,000 SVOs). It will show how narrative data lend themselves to cutting-edge tools of data visualization and analysis as network graphs and maps in Google Earth and other GIS software. It will also show how QNA data provide the basis for fascinating digital humanities projects.
A growing body of research using both behavioral and neuroimaging data points to a significant effect of bilingualism on cognitive outcomes across the lifespan. The main finding is evidence for the enhancement of executive control at all stages in the lifespan, with the most dramatic results being maintained cognitive performance in elderly adults, and protection against the onset of dementia. A more complex picture emerges when the cognitive advantages of bilingualism are considered together with the costs to linguistic processing. I will review evidence for both these outcomes and propose a framework for understanding the mechanism that could lead to these positive and negative consequences of bilingualism.