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Sameer Srivastava

dblp:203/9768 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%
Artificial intelligence
1 paper
Information extraction and text analysis · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational social science and digital humanities › psycholinguistics
linguistic alignment
0.312017
Alignment at Work: Using Language to Distinguish the Internalization and Self-Regulation Components of Cultural Fit in Organizations · ACL (1) 2017

Methods — techniques the papers use, named apart from their topics

directed dynamic alignment measure · 0.6
YearPublicationVenuePosition
2017 Alignment at Work: Using Language to Distinguish the Internalization and Self-Regulation Components of Cultural Fit in Organizations
abstract
Cultural fit is widely believed to affect the success of individuals and the groups to which they belong.Yet it remains an elusive, poorly measured construct.Recent research draws on computational linguistics to measure cultural fit but overlooks asymmetries in cultural adaptation.By contrast, we develop a directed, dynamic measure of cultural fit based on linguistic alignment, which estimates the influence of one person's word use on another's and distinguishes between two enculturation mechanisms: internalization and selfregulation.We use this measure to trace employees' enculturation trajectories over a large, multi-year corpus of corporate emails and find that patterns of alignment in the first six months of employment are predictive of individuals downstream outcomes, especially involuntary exit.Further predictive analyses suggest referential alignment plays an overlooked role in linguistic alignment.
Gabriel Doyle, Amir Goldberg, Sameer Srivastava, Michael C. Frank
ACL (1)3