Sunday, January 11, 2015

Introduction to Sociology (Honors)

SOCI 1500-003 Introduction to Sociology (Honors)

MWF 9-9:50am
Lang 402
January 20-May 15

Associate Professor Gabe Ignatow 
ignatow@unt.edu 
Chilton 390E 
940 565 3616

Assigned book

Introduction to Sociology (Seagull Ninth Edition) Paperback – 2013
by Anthony Giddens, Mitchell Duneier, Richard P. Appelbaum, and Deborah Carr
ISBN-13: 978-0393922233 ISBN-10: 0393922235

Assignments

Assignments are based on both the assigned readings from the textbook and the lectures, which only partially track the textbook.

4 pop quizzes administered in class, 5% each
2 exams, 25% each
1 final exam, 30%

Syllabus

1. Introduction

Read Chapter 1: What is Sociology? (week 1 Jan 21-23)

2. What Is Sociological Research?

Read Chapter 2 Asking and Answering Sociological Questions (week 2 Jan 26-30)

quiz 1

3. Culture and Society

Read Chapter 3: Culture and Society (week 3 Feb 2-6)

quiz 2

4. Groups, Networks, and Organizations

Read Chapter 6: Groups, Networks and Organizations (week 4 Feb 9-13)

exam 1 (week 5 Feb. 20 in class)

5. Social Inequality

Read Chapter 8: Stratification, Class and Inequality (week 6 Feb 23-27)

Read Chapter 9: Global Inequality (week 7 March 2-6)

quiz 3

Read Chapter 10: Gender Inequality (week 8 March 9-13)

spring break

Read Chapter 11: Ethnicity and Race (week 9 March 23-27)

exam 2 (March 27)

6. Work and Economic Life

Read Chapter 14. Work and Economic Life (week 10 March 30-April 3)

7. Sociology of Education

Read Chapter 16: Education  (week 11 April 6-10)

quiz 4

8. Sociology of Religion

Read Chapter 17: Religion  (week 12 April 13-17)

9. Sociology of Globalization

Read Chapter 20: Globalization and a Changing World  (week 13 April 20-24)

Week 14 April 27-May 1 flex week and final exam review

final exam (not cumulative)

Sunday, June 22, 2014

SOCI 5260/6500: Text Analysis

Summer II 2014

M,T,W,Th, 12-1:50pm, Wooten Hal 116, July 7-August 8, 2014

Professor Gabe Ignatow
gignatow@gmail.com

Although this course has a room assigned, it is online-only. We will communicate by email, supplemented by several in-person meetings.

Course description: Social media sites generate massive volumes of natural language data that are available for social science research, and social scientists have developed a number of new technologies for analyzing this data. Researchers are scaling up traditional research techniques to take advantage of new sources of textual data, as well as developing new methods along with new theoretical and metatheoretical frameworks and approaches to research ethics. This course provides a practical guide to contemporary text mining and analysis for the social sciences, covering both qualitative and quantitative text analytic research methods. Our focus in this course is mainly on sociological text analysis methods, including computer-assisted qualitative methods, semantic text analysis methods, and topic models.

Requirements:
1) Completion of weekly assignments (see below)
2) Completion of 10-page final paper

Final paper requirements: 

The final paper can be a proposal for a text mining and analysis project, a completed text mining and analysis project, or somewhere in between. For all final papers, students must collect their own data and explain and justify their sampling strategy. For CAQDAS projects, students must develop a coding scheme and apply it to a sub-sample of the larger text sample. For projects using more highly automated methods, students must review relevant text analysis methods and propose a strategy that can yield results relevant to the research question.

10 pages inclusive of full references, 12-pt font, double-spaced


WEEK 1: INTRODUCTION AND TEXT MINING




Assignments: send by email to gignatow@gmail.com by 12pm Friday July 11
1) Propose one or more research questions that could be approached with text analysis methods
2) Identify 3 or more possible data sources, including newspaper archives, historical archives, social media platforms, websites, or research databases.

(15 points)

WEEK 2: TEXT MINING AND CAQDAS

1. Text Mining


Text mining packages (free) (check YouTube for tutorials)


2. CAQDAS




Free trials of CAQDAS packages (check YouTube for tutorials)


Assignments: send by email to gignatow@gmail.com by 12pm Friday July 18
1) Scrape or otherwise create a text sample of at least 5000 words. Describe the sample and how you collected it.
2) Write a 1-2-page memo describing possible coding schemes you will use on your data.

(15 points)

WEEK 3: SEQUENCE ANALYSIS METHODS
Franzosi 1987 From Words to Numbers
Franzosi 1998 Narrative Analysis

Assignments: send by email to gignatow@gmail.com by 12pm Friday July25
1) Write 1-2-page reviews of two of this week's articles
2) Write a 1-page update of your progress on your final paper

(10 points)

WEEK 4: SEMANTIC AND SENTIMENT ANALYSIS

Bail 2012 The Fringe Effect

Assignments: send by email to gignatow@gmail.com by 12pm Friday Aug 1
1) Write 1-2-page reviews of two of this week's articles
2) Write a 1-page update of your progress on your final paper

(10 points)

WEEK 5: TOPIC MODELS

August 4 Mohr and Bogdanov 2013 Topic Models--What They Are and Why They Matter
August 5-6 Mohr, Wagner-Pacifici, Breiger and Bogdanov Graphing the Grammar of Motives in National Security Strategy

Assignments:
Email presentations to gignatow@gmail.com and ignatow@unt.edu by 5pm August 7 (10 points)
Final paper due by email by 12pm Friday August 8 (40 points)

Wednesday, May 28, 2014

Internet and Society
4260/5260

Review Sheet
Final Exam
5/29/2014

Hargittai, Gallo, and Kane
Clay Shirsky
Sobieraj and Berry
Ignatow and Williams

lowered barriers
organizational reinforcement
social movement coordination
TRCP
VNST
TrinityVote
Angela Hunt
TCE
Dallas Sierra Club
Dallas Citizens Council
Trinity Trust Foundation
Trinity Commons Foundation
Save the Trinity
The Eppstein Group

Arab Spring
Mohammed Bouazizi
Egypt
Tunisia
“dictator’s dilemma”
“conservative dilemma”
propaganda
censorship
silencing
civil society
international viral diffusion
international coordination
“Internet freedom”
instrumental approach
environmental view

media diversification
political fragmentation
social media fragmentation
political polarization
homophily
the blogosphere
“deliberative democracy”
traditional (legacy) news organizations
local monopolies or oligopolies
one-to-many “broadcast model”
“we write, you read” model
democratizaton of news production
user-generated news and opinion
challenge to newspaper business models from free online content
hyper-partisanship
incivility
false information
false outrage
emotional manipulation
cable news
blogs
partisan news websites
network news
“echo chamber”
outrage and incivility

“anchor baby”
small low-threshold sites
medium-size medium-threshold sites

large high-threshold sites

Week 3 lecture notes

Week 3

Politics and Revolution

A

B



Major concepts:

lowered barriers

            new opportunities, tools for individuals and civil society groups and organizations
            for grass roots rather than elite groups

organizational reinforcement
           
            another type of digital divide

social movement coordination (e.g. Arab Spring, OWS, living wage movement)

“dictator’s dilemma”
“conservative dilemma”
            shared awareness
            self-interest
            intertwined economic interests and new media

propaganda
censorship
silencing

civil society

international viral diffusion (e.g. Arab Spring)
international coordination

“Internet freedom”
            instrumental approach
            environmental view

diversification?
political fragmentation
social media fragmentation (e.g. MySpace and FB)
political polarization
homophily
the blogosphere
“deliberative democracy”










The News

the internet and new media have radically transformed news media over the last 20 years

challenged traditional (legacy) news organizations’ business models
            based on local monopolies or oligopolies, limited competition
            one-to-many broadcast model
                        “we write, you read” model

democratizaton of news production

explosion of user-generated news and opinion

challenge to newspaper business models from free online content

as with the internet as a whole, early excitement has given way to concern about the quality of public deliberation, the authenticity of online news and news commentary

concerns about hyper-partisanship, incivility, false information, false outrage, and manipulation of readers’ emotions


television and print news outlets have responded to the new media landscape in several ways

one major trend is media differentiation

different media outlets cater to fragmented audiences who can be targeted by their ideological positions and lifestyles

more consumption of cable news (MSNBC, Fox News), blogs, partisan news websites

less consumption of network news

this is thought to have led to an “echo chamber” dynamic

and an increase in outrage and incivility
            Sobieraj and Berry coded several media sources in terms of:

insulting language, name calling, emotional display, emotional language, verbal fighting/sparring, character assassination, exaggeration, mockery/sarcasm, conflagration, ideologically extremizing language, slippery slope, belittling, use of obscene language

political pundits who make use of these techniques get high ratings and mega-salaries (in the tens of millions): Keith Olbermann, Rachel Maddow, John Stewart, Bill O’Reilly, Glenn Beck


Ignatow and Williams. 2011. New Media and the ‘Anchor Baby’ Boom.

In 2010 the term “anchor baby” came to be commonly used in US media

A racist and inflammatory term

Previously used only by small, extreme, anti-immigrant right-wing groups

How did it enter mainstream news? What is the back story? What is the role of new media in this phenomenon?

Was it due to mainstream news outlets?


Was it due to the blogosphere?


We did a bunch of web analytics and found that the anchor baby meme travelled from small low-threshold sites to medium-size medium-threshold sites and then on to large high-threshold sites.


Basically the trajectory of the AB meme shows how the organizational ecology of US news media has eliminated structural holes that once existed between fringe and mainstream news organizations. It is possible to track memes travelling across this organizational network, but also to track people travelling across it, for example who interviews whom or cites whose study or book on what website or television show.