Sentences with phrase «text analysis model»

Using a text analysis model, they identified common phrases and words in the conversations they examined.

Now, one of the key assumptions of all (more accurately: most) text analysis models is the bag - of - words assumption.

Not exact matches

In the first place, one can note that in the history - of religions school, the model of evolution was applied to the analysis of biblical texts.

To assess the robustness of the results of our regression analysis, we performed covariate adjustment with derived propensity scores to calculate the absolute risk difference (details are provided in the Supplementary Appendix, available with the full text of this article at NEJM.org).14, 15 To calculate the adjusted absolute risk difference, we used predictive margins and G - computation (i.e., regression - model — based outcome prediction in both exposure settings: planned in - hospital and planned out - of - hospital birth).16, 17 Finally, we conducted post hoc analyses to assess associations between planned out - of - hospital birth and outcomes (cesarean delivery and a composite of perinatal morbidity and mortality), which were stratified according to parity, maternal age, maternal education, and risk level.

We differentiated between computational approaches (either based on volume data, such as the number of mentions related to a party or candidate or the occurrence of particular hashtags; or endorsement data, such as the number of Twitter followers, Facebook friends or the number of «likes» received on Facebook walls), sentiment analysis approaches, that pay attention to the language and try to attach a qualitative meaning to the comments (posts, tweets) published by social media users employing automated tools for sentiment analysis (i.e., via natural language processing models or the employment of pre-defined ontological dictionaries), and finally what we call supervised and aggregated sentiment analysis (SASA), that is, techniques that exploit the human codification in their process and focus on the estimation of the aggregated distribution of the opinions, rather than on individual classification of each single text (Ceron et al. 2016).

For example, the combination of computerised text analysis techniques and Big Data now allows us to model millions of texts in a matter of hours.

«Building on the empirical analysis of ego level and language will provide us with a deeper understanding of ego development, its relationship with other models of personality and individual differences, and its utility in characterizing people, texts and the cultural contexts that produce them,» said Lanning.

Creating a novelty of their own, they adapted a computer science text analysis technique called «topic modelling,» for their analysis.

As described in the main text, ordered logistic regression analyses were carried out for each brain region in which social network distances were modeled as a function of local neural response similarities and dyadic dissimilarities in control variables (gender, ethnicity, nationality, age, and handedness).

Differentiation: purple = lower ability blue = middle ability yellow = higher ability Resources prepare students for answering Q3 (language) and Q4 (comparison) and cover the following: - analysis of vocabulary - analysis of sentence forms - analysis of language techniques - explore audience and purpose - study of model answers - exploring the effect of language - improving exam responses using mark schemes - explore perspective - understand the difference between synthesis and comparison - form comparisons between texts - practice timed responses Regular assessments are included to assess students ability in true or false and synthesis tasks.

Students learn through the following tasks: - Gauging and collaborating previous knowledge through an interactive starter task; - Identifying the descriptive devices in sentences written about 19th Century characters; - Building close reading skills through a study of a fiction extract from Frankenstein - Answering exam - style questions interpreting and inferring the key meanings in the text; - Using models and templates to write extended analysis responses about the descriptive language used in the fiction extract; - Peer assessing their partners» learning attempts.

PROSE Award, Honorable Mention, Mathematics and Statistics, Association of American Publishers, Professional and Scholarly Division, for an outstanding professional, reference, text or scholarly work for Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence, (2003)

Scholarship about the relationship between policy leadership and complex social change presents three main images.241 A technical policy perspective is found in most policy analysis texts; it is generally associated with rational choice models.242 Policy leaders should, according to this perspective, focus on rational choices to be made once a policy issue is on the agenda.

The file contains Supplementary Text on the 2D Model, MLS ozone data analysis and Ozone production and destruction rates.

Overall, this work is accessible to a general audience; however, Randers's limited analysis and justification of model assumption restrict the usefulness of this book as a stand - alone text.

Integrated Method for Policy Making Using Argument Modelling and Computer Assisted Text Analysis

Core Competencies Mil - Std - 1553 • Team Leadership • Strategic Analysis • Communications • Product Lifecycle & Development DOORS7 / DOORS8 / DOORS9 • RTOS Embedded System Design Development Waterfall Method • Graphics 2000 Rational Requisite Pro • Rational Clear Quest • Rational Clear Case • Subversion • Matlab • Negotiation • Mentoring • Analysis & Planning • Budget Adherence • ARINC Specification 429Part 1 - 16 • ARINC Specification 702A - 1 DO - 178B • ViaSat DOCCT / S DAMA Simulator • Process Streamlining • DoD - 4650 • UIC • Mil - Std - 461 • Model SIM • DO - 160 • VHDL Text Pad • Ultra Edit • MS Office Suite