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Joe & Doug Bond Class 7 March 24, 2014

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1 Joe & Doug Bond Class 7 March 24, 2014
SSCI E-100b Graduate Research Methods and Scholarly Writing in the Social Sciences: Government and History (23667) Joe & Doug Bond Class 7 March 24, 2014

2 Agenda Announcements Midterm Review Content Analysis
Discuss Tonight’s Readings 7th In-Class Writing Assignment

3 Announcements I have posted a sample literature review on the course website. Use the “Doing a Literature Review” reading as your guidelines. We will get your book reviews back to you by the end of the day tomorrow.

4 Facilitator Assignments
3/31/2014 (Don Ostrowski will speak next week) Need Lina 4/14/2014  Mohra, Sadiq, JD 4/21/2014  Albana, Shawn

5 Tonight’s Reading 1st half of Historians’ Fallacies & history handouts Facilitator: Andrew

6 Content Analyze This!

7 Content Analysis Content Analysis is a systematic attempt to examine some form of verbal or visual communication such as newspapers, diaries, letters, speeches, movies, or television. Can be inductive or deductive. Objective is to classify content Can be either qualitative or quantitative (e.g. frequency counts). Manifest Content: what explicitly appears in a text. Latent Content: meanings implied by the written content that do not actually appear in the text.

8 Examples Content Analysis of Video Games
Look at “E” (like rated G) games and look for violence, killing, and the use of weapons in the course of normal play. Analyze The Daily Show and Assess for: % of the stories addressing political topics % of the stories addressing a public policy theme % of the stories addressing international news in some way % of the stories having to do with the news media % of the stories that address celebrity/entertainment news % of the guests who could be labeled serious (e.g. politicians, government officials, authors, etc.) % of stories that involved traditional news media or video footage vs. % coming from network of cable news shows

9 Group Exercise Identify as many themes as you can associated with each ad Rate the intensity of each theme as it corresponds to that particular ad


11 Verbal Behavior Analysis
Verbal Behavior Analysis (VBA) is a content analytic technique designed to tap "styles of speaking with patterns of thinking and behaving" (Weintraub, 1989: 7). Weintraub devised a system to analyze samples of speech (monologues elicited by a standardized procedure) to obtain the frequencies of occurrence of members of fourteen categories, not all of which are, strictly speaking, "syntactic" (e.g. long pauses and the rate of speech). Then groups representing "no pathology" and various psychopathological syndromes are compared with respect to the frequencies with which these categories appear in speech.

12 VBA, Continued Fifteen indicators: 1) I, 2) We, 3) Me, 4) Negatives, 5) Qualifiers, 6) Retractors, 7) Direct References, 8) Explainers, 9) Expressions of Feeling, 10) Evaluators, 11) Adverbial Intensifiers, 12) Non-personal References, 13) Creative Expressions, 14) Rhetorical Questions, and 15) Interruptions

13 VBA, Continued frequent use of evaluators are indicative of individuals possessing a punitive conscience frequent use of retractors convey impulsivity high adverbial intensifier scores indicate persons "who see the world in black and white terms;" frequent use of explainers signify tendencies toward rationalization high qualifiers scores indicate anxiety and avoidance to commitment frequent use of negatives signify negation and denial frequent use of rhetorical questions indicate aggressiveness frequent use of direct references indicates that the speaker has difficulty speaking and prefers to divert the attention of the audience low use expressions of feeling convey an impression of aloofness frequent use of creative expressions indicate creativity

14 Quick PT Analyzer

15 Content Analysis of Newsfeed

16 Integrated Data for Events Analysis (IDEA): A Third Generation Event Framework
Most domain specific events data frameworks have been or can be mapped to IDEA, including WEIS, PANDA, MIDS, etc. IDEA is a multi-framework compatible data standard designed to facilitate the comparison of data developed by different conceptual frameworks The IDEA framework is currently comprised of 249 social, economic, environmental and political events WEIS started in the 1960s by McClelland. WEIS includes 22 cue categories and 61 events. PANDA used the 22 WEIS cue categories and 135 events

17 IDEA Class Hierarchy (N=249)
Level 0: All phenomena Level 1: Animal incidents, Human actions, Human conditions, Other incidents Level 2: Animal attack, Accident, Accuse, Animal death, Agree, Animal illness, Cognitive state, Complain, Consult, Human death, Demand, Demonstrate, Deny, Economic activity, Endorse, Economic status, Expel, Force Use, Grant, Human illness, Natural disaster, Other animal incident, Other human action, Other human condition, Other incident, A&E Performance, Promise, Propose, Reject, Request, Reward, Comment, Sanction, Seize, Sports contest, Threaten, Warn, Yield Level 3: Abduction, Affective state, Agree or accept, Alerts, Promise to mediate, Apologize, Arrest and detention, Ask for material aid, Request protection, Assure, Beliefs and values, Criticize or denounce, Balance of payments, Break relations, Call for action, Unconventional weapons attack, Acknowledge responsibility, Extreme climactic condition, Collaborate, Crowd control, Commodity prices, Demand aid, Decline comment, Demand ceasefire, Default on payment, Defy norms, Demand information, Demand mediation, Demand meeting, Demand protection, peacekeeping, Demand policy support, Demand rights, Demand withdrawal, Discussion, Drought, Declare war, Corporate Earnings, Earthquake, Ease sanctions, Extend economic aid, Extend humanitarian aid, Extend military aid, Empathize, Equity prices, Exchange rates, Formally complain, Flood, Forgive, Executive adjustment, Halt discussions, Infectious human illness, Host a meeting, Hurricane, Informally complain, Improve relations, Interest rates, Extend invitation, Judicial actions, Armed force blockade, Armed force mobilization, Armed force display, Covert monitoring, Armed force threats, Non-infectious human illness, Other physical force threats, Radioactive leak, Optimistic comment, Physical assault, Pessimistic comment, Protest demonstrations, Praise, Promise material support, Promise policy support, Offer to mediate, Offer to Negotiate, Offer peace proposal, Armed actions, Refuse to allow, Ratify a decision, Real estate prices, Reduce or stop aid, Reduce routine activity, Release or return, Currency reserves, Riot Reject proposal, Investigate Seize possession, Provide shelter, Solicit support, Hazardous material spill, Rally support, Strikes and boycotts, Tornado, Transactions, Sanctions threat, Tsunami, Non-specific threats, Give ultimatum, Travel to meet, Volcano, Elect representative, Wildfire, Yield to order, Yield position Level 4:Armed force air display, Missile attack, Ask for economic aid, Ask for humanitarian aid, Ask for armed assistance, Assassination, Agree to mediation, Agree to negotiate, Agree to peacekeeping, Agree to settlement, Impose restrictions, Beatings, Border fortification, Break law, Armed force border violation, Chem-bio attack, Private transactions, Private default on payments, Impose censorship, Armed battle, Bodily punishment, Coups and mutinies, Criminal arrests, De-mining, Demobilize armed forces, Earnings above expectations, Earnings below expectations, Ease economic sanctions, Ease military blockade, Equity prices down, Equity prices up, Evacuate victims, Grant asylum, Government transactions, Government default on payments, Artillery attack, Reduce or stop humanitarian assistance, Halt negotiation, Halt mediation, Reduce or stop economic assistance, Political flight, Reduce or stop military assistance, Reduce or stop peacekeeping, Hostage taking and kidnapping, Investigate human rights abuses, Security alert, Downward trend in interest rates, Investigate war crimes, Upward trend in interest rates, Hijacking, Torture, Armed force alert, Mediate talks, Mine explosion, Armed force activation, Armed force occupation, Armed force naval display, Engage in negotiation, Nuclear alert or test, Disclose information, Protest altruism, Small arms attack, Protest procession, Political arrests, Protest obstruction, Protest defacement, Promise economic support, Promise humanitarian support, Promise military support, Reject ceasefire, Relax curfew, Request mediation, Request an investigation, Reject mediation, Nuclear attack, Reject peacekeeping, Reject proposal to meet, Relax censorship, Reject request for material aid, Return, release person(s), Return, release property, Relax administrative sanction, Reject settlement, Request withdrawal or ceasefire, Suicide bombing, Sexual assault, Threaten forceful attack, Threaten forceful blockade, Threaten to boycott or embargo, Threaten biological or chemical attack, Armed force troops display, Threaten to halt negotiations, Threaten to halt mediation, Threaten nuclear attack, Threaten forceful occupation, Threaten to reduce or break relations, Threaten to reduce or stop aid, Observe truce, Threaten war, Vehicle bombing, Veto Contrast WEIS’ two-level structure with IDEA’s five-level structures. Note: In IDEA, level 3 events are analogous to WEIS cue categories. Whereas WEIS consisted of 22 cues, IDEA contains 38. All 22 original WEIS cues are contained in the level 3 IDEA events.

18 Selected Branches (IDEA Event Framework)
All phenomena Human action Human conditions Animal incidents Other incidents Other human condition Human illness Economic status Human death Cognitive state Infectious human Non-infectious Affective state Beliefs illness human illness and values Balance Commodity Debt Equity Exchange Real Currency reserves of payments prices yields prices rates estate prices Red signifies a terminal event (i.e., the lowest node on a branch) 4 under animal incidents animal attack, animal death, animal illness and other animal incident. None under other incident. There are 16 events subsumed under human conditions = – 23 = 176 (88.4%) events that involve human action.

19 Basic Structure of Extracting Meaning from a Report
Subject Verb Direct Object/Indirect Object Examples: US President Barack Obama blasted Russian President Vladimir Putin for annexing Crimea. The U.S. delivered $20 million of humanitarian aid to South Sudan yesterday. Subject (source), Verb (event), Direct Object/Indirect Object (target) The basic formula used to extract the basic meaning of news reports is to associate a subject of the sentence with a verb of the sentence with a direct or indirect object of the sentence. In this way, we extract the basic parameters of who did what to whom. Two examples illustrate this procedure: Bush is the subject of the first sentence and also the source of the interaction (i.e., the who) Blasted is the verb of the sentence or the event interaction. This could be translated into an event form loosely labeled as blame or criticize. Finally, Saddam Husein is the direct object of the sentence (i.e., the whom). Sometimes the target of the event interaction is not the direct object of the sentence but rather the indirect object of the sentence. In the second example, humanitarian aid is the direct object of the sentence but we don’t want to pick up the humanitarian aid as the target of the event interaction. Instead we want to pick up Afghanistan (the recipient of the aid) as the target so we pick up the infinitive (to Afghanistan) and map it to the target of the event interaction which translates into “extend humanitarian aid.” In this way the sentence is resolved as US (source) extending humanitarian aid (event interaction) to Afghanistan (target). In full-frame syntax parsing, we rarely enter literals in the protocol. For example, we don’t enter George W. Bush in our dictionary because we know, by virtue of his title, US President, that he is the national executive of the United States. Instead we rely on noun classes, which I will discuss shortly.

20 Variables Coded from Each Clause
1) ID (auto-generated, unique ID, 2) Sentence ID, 3) Event ID, 3) Event Date, 4) Report Date, 5) Event Place (e.g. Baku), 6) Event Administration (e.g. Azerbaijan), 7) Source Value (e.g. President Ilham Aliyev 's grip), 8) Source Name (e.g. AZJ), 9) Source Administration (AZJ), 10) Source Level (e.g. INDI), 11) Source Sector (e.g. NEXE), 12) Event Negated, 13) Event Status (e.g. past, ongoing, foreshadowing), 14) Event Type (e.g. conflict/cooperation), 15) Is Flagged (i.e. pre-defined search terms), 16) Event Form (i.e. IDEA code, 17) Event Value (literal value), 18) Target Value (literal value), 19) Target Name, 20) Target Admin, 21) Target Level, 22) Target Sector, 23) Information Value, 24) Information Name, 25) Information Admin, 26) Information Level, 27) Information Sector, 28) Locus, 29) Affect, 30) Mechanism, 31) Injury, 32) Damage From these 32 variables we create 50 + additional variables in a post-parse process

21 Example Description of an IDEA Event Form
IDEA Event Code: 2122 Name: Criminal arrests and detentions Description: Arrests and detentions explicitly characterized as criminal Usage Notes: Example*: French police on Tuesday arrested a man trying to sneak through Paris airport customs with a boa snake hidden in his underpants, an airport spokeswoman said. *Source = blue, Event = red and Target = green Source Literal French Police Sector Police Level Organization Association France Target a man Nominal Individual None Go through this example. Try the passive, “a man was arrested today” and “a man was arrested by police today.” Also “X gave something to Y”; since we don’t have an event that captures someone giving something to someone, we swap the source and target and make it someone extending aid to someone else. Some events are reciprocal by definition. A discussion, for example, implies at least two parties are involved. Thus X discussed something with Y constitutes 2 discrete events X discuss with Y and Y discuss with X. 3 parties in a discussion produces discrete events. Another example of a reciprocal event is a military clash. Other events are linked by not reciprocal. Traveling to meet someone is linked to host a visit and visa versa.

22 Wordnet’s 15 Senses for the Verb “kill”)
1. kill -- (cause to die; put to death, usually intentionally or knowingly; "This man killed several people when he tried to rob a bank"; "The farmer killed a pig for the holidays") 2. kill, defeat, vote down, vote out -- (thwart the passage of; "kill a motion") 3. kill -- (cause the death of, without intention; "She was killed in the collision of three cars") 4. stamp out, kill -- (end or extinguish by forceful means; "Stamp out poverty!") 5. kill -- (be fatal; "cigarettes kill"; "drunken driving kills") 6. kill -- (be the source of great pain for; "These new shoes are killing me!") 7. kill -- (overwhelm with hilarity, pleasure, or admiration; "The comedian was so funny, he was killing me!") 8. kill -- (hit with so much force as to make a return impossible, in racket games; "She killed the ball") 9. kill -- (hit with great force, in sports; "He killed the ball") 10. kill -- (deprive of life; "AIDS has killed thousands in Africa") 11. toss off, bolt down, belt down, pour down, down, drink down, kill -- (drink down entirely; "He downed three martinis before dinner"; "She killed a bottle of brandy that night") 12. kill, obliterate, wipe out -- (mark for deletion, rub off, or erase, as of writings; "kill these lines in the President's speech") 13. kill -- (tire out completely; "The daily stress of her work is killing her") 14. kill -- (cause to cease operating; "kill the engine") 15. kill -- (destroy a vitally essential quality of or in; "Eating artichokes kills the taste of all other foods") See WordNet As you can see, there are 15 discrete senses for the verb kill in the English language. The senses are arrayed probabilistically. Thus, sense 1, cause to die, put to death is the most commonly invoked sense of the verb kill (i.e., one U.S. soldier was killed yesterday in fighting with suspected al-Qaida and the Taliban. Sense 2, to defeat, vote down, vote out is the second most commonly invoked sense of the verb kill (the Senate killed the bill). is an online lexical reference system English nouns, verbs, adjectives and adverbs are organized into synonym sets, each representing one underlying lexical concept. Different relations link the synonym sets.

23 Sense 2 "Hypernyms (this is one way to...)" of verb "kill"
kill, defeat, vote down, vote out -- (thwart the passage of; "kill a motion veto, blackball  -- (vote against; refuse to endorse; refuse to assent) oppose, controvert, contradict - (be resistant to; "The board opposed his motion.“ refute, rebut - (overthrow by argument, evidence, or proof; “the speaker refuted his opponent's arguments") renounce, repudiate (cast off or disown; "She renounced her husband“) reject -- (refuse to accept or acknowledge; "I reject the idea of starting a war"; "The journal rejected the student's paper") judge -- (form an opinion of or pass judgment on) This slide shows the hypernyms associated with sense 2 of the verb kill. A hypernym is simply a superordinate word -- (a word that is more generic than a given word). We can see on this slide that the verbs kill, defeat, vote down, vote out are subordinate to the verbs veto and blackball. These verbs, in turn are subordinate to the verbs oppose, controvert and contradict and so on. The words in red represent a synset associated with sense 2 of the verb kill. That is, the words appearing in red constitute a container of words that we invoke in the protocol. For example, rather than select Jim killed Bill (with a capital B), we simply invoke sense 1 of the verb kill and associate it with any true agent as a source and any true agent as a target and map it to a physical assault. Similarly, for the sentence the Senate killed a bill (with a small b), we invoke sense 2 of the verb kill (along with the corresponding synset of verbs associated with that sense) and map it to a subject with a noun class of national legislature and a target using the noun class legislation, which includes the noun bill.

24 Sense 2: Container (synset) of verb "kill"
judge reject renounce; repudiate refute; rebut oppose; controvert; contradict veto; blackball kill; defeat; vote down; vote out

25 Semantic Framework: Noun Classes
Top Level All agents Level 1 True agents (political actors) Pseudo agents (other actors, like the environment) Level 2 Civil society agents, Government agents Intangible things, Tangible things Level 3 Armed civilian groups, Artists, Athletes, Body parts, Communication, Events, Human actions, Businesses, Candidates, Civic group agents, Human artifacts, Human cognition, Human attitudes, Criminals, Detainees, Diplomats, Educators, Natural environment, Status, Time-related Ethnic agents, Farmers, Health care agents, phenomena Judiciary, Legislators, Mass media, Migrants, Military, National executive, Nominal agents, Occupations, Officials, Political opposition, Political parties, Philanthropic agents, Religious agents, Royalty, Sub-national officials, Students, Unions Level 4 Arabs, Bosnian-Croats, Bosnian-Moslems, Animals, Ancient beliefs, Disease, Bosnian-Serbs, Christians, Cult, Christian-Orthodox, Food, Health conditions, Historical figures, Hindu, Insurgents, Jew, Kurds, Moslems, Ideology, Human languages, Legislation, Peace-keeping forces, Paramilitary groups, Location, Markets, Human-made Police (note that the entries at this level are for conditions, Monetary units, Non-gun weapons, illustration purposes only; a comprehensive list of Protest actions, Plants and flora, Polls & surveys, entries is included in actual data development) Travel to meet, Violent actions, Weapons, Weather conditions Level 5 (greater differentiation among agents is possible Accident, Apology, Assassination, Balance of through user specification) payments, Biological agent/weapon, Bombing action, CBR weapons use, Censorship, Chemical agent/weapon, Commodity prices, Debt yields, Drought, Earthquakes, Equity prices, Exchange rates, Explosive device, Floods, Firearms, Harassment, Hurricanes and typhoons, Infectious disease, Litigation, Military actions, Military hardware, Monetary reserves, Nuclear devices, Protest altruism, Real estate prices, Military raids, Riot, Rapes, Shooting, Strike and boycott action, Tornados, Tsunami, Volcanic events, Wild fires Level 6 Biological weapons use, Car bomb, Car bombing, De-mining vehicle, Grenade/RPG, Grenade/RPG use, Mine explosions, Mines, Missile, Missile attack We follow a similar hierarchy with nouns as we do with verbs The semantic class hierarchy utilizes a one-to-many relationships. At level one we have true agents and pseudo agents. Tangible and intangible things (level 2) are subsumed under pseudo agents. Human actions is a sub of tangible things (level 3) Violent actions (level 4) is a sub of human actions And CBR weapons (level 5) is a sub of violent actions Finally biological weapons use (level 6) is more specific than CBR weapons use and is, therefore, subsumed in the CBR weapons use container. Now anytime we want to specify a violent action as a source or target of an event interaction, we simply invoke the class violent action (which may include thousands of nouns and noun phrases like fighting, beating, hitting, biting, clobber, smack, etc.) and we pick up every conceivable forms of violent actions. Because CBR weapons use is mapped to a unique IDEA event form class (CBR weapons use), we drop down to level 5 or 6 to accommodate this mapping. In other words, we save our selves many a lot of protocol development work in that we specify what we want with one line of code as opposed to dozens or hundreds of lines. Take this example: X discussed something with Y. It doesn’t matter who X or Y are. The event will always be discussion. So we can simply invoke the container true agent which includes all human beings and their titles. In other words, a car thief, a president, a lawyer, a nurse, a doctor will all be picked up.

26 Synset Example: Selected Entries of Nouns and Noun Phrases Mapped to the Noun Class “Migrant” (WordNet) abandoned, abandoned person, bag lady, beggar, beggarman, beggarwoman, bird of passage, bum, castaway, deportee, derelict, displaced person, internally displaced person, dosser, down-and-out, DP, IDP, drifter, evacuee, exile, foundling, gamin, have-not, hobo, homeless, homeless person, immigrant, mendicant, migrant, nomad, orphan, outcast, outcaste, panhandler, pariah, poor person, profligate, ragamuffin, rake, refugee, rip, roamer, roue, rover, shipwreck survivors, quatter, squatter, stateless person, street arab, street person, sundowner, tatterdemalion, throwaway, tramp, transient, urchin, vagabond, vagrant, waif, wanderer KEDS/TABARI dictionary is below 10,000 entries. We use all of WordNet plus selected additions like al-Quida, Osama bin Laden, etc. Our sense index is now approaching 187,000 entries. Each of the 187,000 entries are assigned a sector and level of association, where appropriate. We then invoke these classes rather than literals whenever possible. In fact, relatively speaking we have very few literals in our protocol. This is perhaps the biggest difference from KEDS/TABARI. With KEDS/TABARI, the software scoops up selected events contingent on entries made to the dictionary. At least 1/3 of KEDS/TABARI dictionary entries are used to EXCLUDE events. In other words, they are added in order to avoid false positives. We use no such entries. Because the IDEA framework is theoretically all-inclusive (i.e., it was designed to capture all phenomena), it theoretically picks up all reported events. In this sense we are fishing with very large nets whereas sparse parsers like KEDS/TABARI are fishing with poles and a specific kind of bait used to attract specific kinds of fish.

27 From Syntax to Events The Reader generates and maps “events,” or who does what to whom when where & how syntax (from the read module) semantics (from an external dictionary) and user-specified information (from a protocol) into data matrices that can be used in statistical and other analyses.

28 Mapped to (user defined) Events
The mapping procedure is guided by a user-defined set of dictionaries or protocol. The (IDEA) protocol maps specific words and phrases to their various meanings. Relevant behavioral referents are considered events, around which the event data matrix is built. Each event is linked to its actors who are identified as individuals, groups, organizations or states.

29 The Reader & IDEA Operate together to support monitoring and interactive assessment of evolving conflict situations, In other words, what you will see in the Visualizer is not the end of the story. It is the beginning of the story for the analyst.

30 Automated Coding Advantages of automated coding no longer in dispute (exceptions: idiosyncratic text, low N) As good as humans (see King and Lowe article “An Automated Information Extraction Tool for International Conflict Data with Performance as Good as Human Coders: A Rare Events Evaluation Design” in International Organization, Vol. 57, No. 3, pp , July 2003) 100% Consistent (could be consistently bad but it is consistent) 100% Transparent Flexible & Extensible

31 Recall, the Reader is one of three components that make up the Knowledge Manager. The Reader is a full-syntax frame parser that Protocol is opposition (noun class) boycotts a social actions (noun class).





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