An Active Analysis and Crowd Sourced Approach to Social Training

نویسندگان

  • Dan Feng
  • Elín Carstensdóttir
  • Sharon Marie Carnicke
  • Magy Seif El-Nasr
  • Stacy Marsella
چکیده

Interactive narrative (IN) has increasingly been used for social skill training. However, extensive content creation is needed to provide learners with flexibility to replay scenarios with sufficient variety to achieve proficiency. Such flexibility requires considerable content creation appropriate for social skills training. The goal of our work is to address these issues through developing a generative narrative approach that reconceptualizes social training IN as an improvisation using Stanislavsky’s Active Analysis (AA), and utilizes AA to create a crowd sourcing content creation method. AA is a director guided rehearsal technique that promotes Theory of Mind skills critical to social interaction and decomposes a script into key events. In this paper, we discuss AA and the iterative crowd sourcing approach we developed to generate rich, coherent content that can be used to develop a generative model for interactive narrative.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning

Crowd-sourcing has become a popular means of acquiring labeled data for many tasks where humans are more accurate than computers, such as image tagging, entity resolution, and sentiment analysis. However, due to the time and cost of human labor, solutions that rely solely on crowd-sourcing are oŸen limited to small datasets (i.e., a few thousand items). is paper proposes algorithms for integrat...

متن کامل

Active Learning for Crowd-Sourced Databases

Crowd-sourcing has become a popular means of acquiring labeled data for many tasks where humans are more accurate than computers, such as image tagging, entity resolution, or sentiment analysis. However, due to the time and cost of human labor, solutions that solely rely on crowd-sourcing are often limited to small datasets (i.e., a few thousand items). This paper proposes algorithms for integr...

متن کامل

Crowd-sourced Text Analysis: Reproducible and Agile Production of Political Data

Empirical social science often relies on data that are not observed in the field, but are transformed into quantitative variables by expert researchers who analyze and interpret qualitative raw sources. While generally considered the most valid way to produce data, this expert-driven process is inherently difficult to replicate or to assess on grounds of reliability. Using crowd-sourcing to dis...

متن کامل

Depeche Mood: a Lexicon for Emotion Analysis from Crowd Annotated News

While many lexica annotated with words polarity are available for sentiment analysis, very few tackle the harder task of emotion analysis and are usually quite limited in coverage. In this paper, we present a novel approach for extracting – in a totally automated way – a highcoverage and high-precision lexicon of roughly 37 thousand terms annotated with emotion scores, called DepecheMood. Our a...

متن کامل

Reducing the Cost of Dialogue System Training and Evaluation with Online, Crowd-Sourced Dialogue Data Collection

This paper presents and analyzes an approach to crowd-sourced spoken dialogue data collection. Our approach enables low cost collection of browser-based spoken dialogue interactions between two remote human participants (human-human condition) as well as one remote human participant and an automated dialogue system (human-agent condition). We present a case study in which 200 remote participant...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016