@article {bib_81,
	title = {Taming big data: Applying the experimental method to naturalistic data sets},
	journal = {Behavior Research Methods},
	volume = {51},
	year = {2019},
	pages = {1619-1635},
	abstract = {Psychological researchers have traditionally focused on lab-based experiments to test their theories and hypotheses. Although the lab provides excellent facilities for controlled testing, some questions are best explored by collecting information that is difficult to obtain in the lab. The vast amounts of data now available to researchers can be a valuable resource in this respect. By incorporating this new realm of data and translating it into traditional laboratory methods, we can expand the reach of the lab into the wilderness of human society. This study demonstrates how the troves of linguistic data generated by humans can be used to test theories about cognition and representation. It also suggests how similar interpretations can be made of other research in cognition. The first case tests a long-standing prediction of Gentner{\textquoteright}s natural partition hypothesis: that verb meaning is more subject to change due to the textual context in which it appears than is the meaning of nouns. Within a diachronic corpus, verbs and other relational words indeed showed more evidence of semantic change than did concrete nouns. In the second case, corpus statistics were employed to empirically support the existence of phonesthemes{\textemdash}nonmorphemic units of sound that are associated with aspects of meaning. A third study also supported this measure, by demonstrating that it corresponds with performance in a lab experiment. Neither of these questions can be adequately explored without the use of big data in the form of linguistic corpora.},
	keywords = {Big data, Corpus statistics, Phonesthemes, Representation, Semantic change},
	doi = {10.3758/s13428-018-1185-6},
	url = {http://link.springer.com/10.3758/s13428-018-1185-6},
	author = {Sagi, Eyal}
}
@article {bib_84,
	title = {Cognition and Emotion in Narratives of Redemption: An Automated Analysis},
	year = {2018},
	address = {New Orleans, LA},
	abstract = {Redemptive narratives are stories of challenge, failure, or adversity that in some way acknowledge the goodness or personal growth that came of the recounted difficult event. In this paper we use a corpus-statistic based approach to explore the role of cognition and emotion in these narrative arcs. In particular, we trace the shift from negative to positive sentiment (a change in the emotional valence) and vice to virtue (evidence of cognitive, moral processing) within the narrative and compare these with similar narratives that do not present a redemptive arc. Our results suggest that the shift to goodness and growth that is at the core of redemptive narratives is driven by prior cognitive processes more so than emotional ones. We believe this type of analysis can also be used to trace and classify similar narrative arcs and assist with the coding of autobiographical narratives in general.},
	author = {Sagi, Eyal and Jones, Brady K.}
}
@conference {bib_82,
	title = {Cognition and Emotion in Narratives of Redemption: An Automated Analysis},
	booktitle = {Proceedings of the 40th Annual Conference of the Cognitive Science Society},
	year = {2018},
	pages = {2382-2387},
	publisher = {Cognitive Science Society},
	organization = {Cognitive Science Society},
	address = {Austin, TX},
	abstract = {Redemptive narratives are stories of challenge, failure, or adversity that in some way acknowledge the goodness or personal growth that came of the recounted difficult event. In this paper we use a corpus-statistic based approach to explore the role of cognition and emotion in these narrative arcs. In particular, we trace the shift from negative to positive sentiment (a change in the emotional valence) and vice to virtue (evidence of cognitive, moral processing) within the narrative. Our results suggest that cognitive processes, more than emotion, drive the shift to goodness and growth that is at the core of redemptive narratives. We discuss the implications of these results to both narrative psychology and cognitive psychology.},
	author = {Sagi, Eyal and Jones, Brady K.},
	editor = {Rogers, T. T. and Rau, M. and Zhu, X. and Kalish, C. W.}
}
@article {bib_85,
	title = {Embodied concept mapping: redefining concepts},
	year = {2018},
	address = {Sydney, Australia},
	author = {Marmolejo-Ramos, Fernando and Khatin-Zadeh, Omid and Yazdani-Fazlabadi, Babak and Tirado, Carlos and Sagi, Eyal}
}
@article {bib_83,
	title = {Language Dynamics in Supreme Court Oral Arguments},
	year = {2018},
	address = {Madison, WI},
	abstract = {During conversations, it is not uncommon to notice that interlocutors start using similar words and grammatical structures. This alignment of language use is thought to help comprehension, as well as lead to an alignment in underlying representations. In the context of negotiations, the degree to which parties exhibit such an alignment can indicate the likelihood of reaching an agreement. The present study expands this notion to the courts and uses corpus statistics to examine the relationship between the alignment of semantic content during oral arguments and the decision reached by the justices. The analysis demonstrates that lawyers that align their language with that of the justices are more likely to have a decision in their favor. Additionally, as befits the power dynamic between justices and lawyers, lawyers are more likely to align their language with the justices than the justices are to align their language to that of the lawyers.},
	author = {Sagi, Eyal}
}
