IULC Indiana University Linguistics Club

What do words do? Towards a theory of language-augmented thought

Time: 04:00pm - 05:00pm 

Place: Psychology Room 101

Gary Lupyan (University of Wisconsin)

In this talk I will focus on a fundamental property of language: using words to refer to objects in the environment. What consequences does such labeling have on cognitive and perceptual processes? To what extent is “normal” human cognition, actually language-augmented cognition? I review evidence indicating that verbal labels actively modulate conceptual representations that are brought online during “nonverbal” tasks. Using words to refer to objects affects the learning of new categories, memory for object details, and reasoning about familiar categories. Strikingly, verbal labels also affect performance on even the most basic visual tasks, with object representations activated verbally seemingly becoming more categorical than ostensibly the same object representations activated nonverbally. Disruptions of linguistic processes likewise appear to affect performance on a variety of apparently nonverbal tasks. Together, the findings point to pervasive effects of language on ongoing cognition and perception.

In category: Child language acquisition

Toward a Pedagogical 'Arab Spring': Teaching and Learning Arabic in the US

Time: 05:00pm - 06:00pm 

Place: Maple Room, Indiana Memorial Union (IMU)

Mahmoud Al-Batal (University of Texas at Austin)

In category: Second language acquisition

Full text citation analysis for scientific recommendation

Time: 12:00pm - 01:00pm 

Place: Memorial Hall 401

Xiaozhong Liu, Jinsong Zhang, and Chun Guo

While different citation analysis studies employed various sophisticated network analysis methods for scientific characterization, the basic assumption was easy and straightforward: either Publication1 cites Publication2, or Author1 cites Author2, regardless of sentiment, reason, topic, or motivation. More recent studies have shown, however, that this assumption is oversimplified. For this proposed research, by using citation context (extract from full-text data), we will characterize each scientific publication/venue/author along with each citation relation on a scholarly network differently by using labeled topic modeling method. More importantly, based on our experiment result, we found full-text citation can significantly enhance the scientific recommendation performance.

http://discern.uits.iu.edu:8790/publication/Full%20text%20citation.pdf

In category: Computational linguistics