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heider’s balance theory

tom petty last dance with mary jane (prod rick rubin)

so i read a couple papers tonight and i genuinely believe i can implement something way better than those.

lately i have been doing a project trying to computationally model social dynamics.

this would entail a social suite.

i should pick some terminology.

agent
actor
party

and then the dsl for partus and conversation turn-taking

basically, for this strange obsessiveness for social interactions to catch on, it has to be done on a group that would want it to be done on it. perhaps i could do something like an “opt-in” for it

where it is acceptable to continue with inits

where it is required to counter with inits

so responding to partus taking about self [{

“required”, “expected”, “warrented”, “unwarrented”, “really unwarrented”

so do these interactions get carried out from sentiment parameters, and then go from there?

where it has a chance of continuing, and where it doesnt, the probability could be

talking about self in same merology in field, where it is warrented to

symbols for themology, merology, idiology

in a merology: it is never required to talk about self [{ in new idiology it is not required but usually expected to talk about self [{ in old idiology : but if you dont talk about self in old idiology enough, it can come off as cold sometimes it is acceptable to talk about self [{ in new idiology, and sometimes it isn’t : the new idiology could become a new local merology? there are times where it is required to talk about other ]} in old idiology

am i trying to simulate turn-taking, or am i trying to simulate what the actual words are going to be?

the MAX probability, it falls in an uncertainty (abused term, sorry) before that

some category theory thing for different “topics”

lack of basic understanding of category theory

for the ego dsl

partus partiality to other partus
themology ratings
- two individual ratings to themology. this is just how interested a partus is to it, not how likely it is to bring it up
  - for example if there is a themos A that iso is very interested in but allo is not interested in at all, than the schelling coefficient for bringing up themos A is going to be pretty low - but it is still “warrented” for iso to bring it up more than allo, as long as the empathetic interest from allo to iso for themos A is high enough. but, if there is a themos B where iso is very interested in it and allo is somewhat interested in it (and lets say interest $\text{iso}_A = \text{iso}_B$ )), than iso will bring up topic B more than topic A because the shelling coefficient is higher.
- inter-partus themos empathetic interest: two individual <-> other rating pairs for themology (how much does iso care about how much allo cares about themology)
- note here it also must be considered so if one person gets another person interested in something and then that other person is interested on their own outside the relationship, than it has escaped the “map rating(?)” (is that what I am going to call it?). but sometimes after the relationships collapses, that person isn’t interested in it at all
- pair rating to themology contains: how likely iso, allo is to bring up themology independently; pair schelling point for themology

on namespace

so if you only have a few terms to describe something on an integral/gradient (for example, themology, merology, specology - these are all gradient/integral and arbitrary definitions), the way to decide where it falls is binary functional tests in a decision tree for terminology classification

operationally rigorous classification boundaries

does this thing usually do this? this? and this? if so, then it falls on this level. if not, then go below. does it do this, this and this? if so, then it falls on this level. if not, then go below.

themology: does it come up in every conversation?
merology: could you have another conversation about this same topic later?
idiology: could you talk about something different while still staying on the same topic?

no im talking about this idology of using recursive functional binary tests decision tree to determine what something should be classified as on arbitrary points on an integral/gradient/continuum
has that been done before
not labeling parts of speech. that's elementary

this could be very impactful. imagine how many "intellectuals" come up with "theories" making a bunch of names for things that all play together kinda when really they should just be using a binary functional tests in a decision tree for classification terminology
"pod" and "node" for kubernetes, a bunch of economic theories (this is a nation, this is a subnation, this is a community, the community has this relation with the subnation and this with the nation...)self-reinforcing cycle of visibility

: claude

dyad – the psychology of interpersonal relations -> this can be an irreducable

is that why knowledge is gatekept? because, anyone with enough time and an iq over 100 can gather knowledge and patternmatch sufficiently. now, if they use that knowledge as a genetic bulwark, than it could pollute the genepool. and gatekeeping is a defense against that.

entitled favor grabber presumptuous favor grabber

A+B;A+C|B+C|A+B+C
A+D;A+E|D+E|A+D+E // this does not bring in the epistemic layer

G1 = {A,B,C}
G2 = {A,D,E}

GL = {G1 U G2}

---

A+B+C
A+D

GL = A+B+C+D

reflexive O> symmetric <-> assumed -> implied -> ->

second rate academics: Hunter S. Thompson

when it comes to

negative

being good with money
being good with dangerous things {knives, fire, food safety}

positive

good at matchmaking
good at setting the vibe
good for protection? (guns)
good at cooking

-> expectation vs. exceptional performance

the Social Attribution Function is:

$f:$ Person $\times$ Behavior -> Sign

where Behaviors $B$ are partitioned into $B_1$ and $B_2$ such that:

For $b \in B_1$ : $f(p,b) \in \{+, /\}$
For $b \in B_2$ : $f(p,b) \in \{/, -\}$

Expectancy Violations Theory is when people only comment when behavior violates expectations. Here I propose some behaviors have asymmetric violation patterns - they can only violate expectations in one direction.

A+B;B/C;A+C
A+B,B/C,A+C
A+B;T(A,B)-;T(B,A)-;

# data restrictions

- american - 20th century or after - mixed gender - well-documented in text-based formats (not image based ones) (this doesn’t exclude artistic circles, it just has to have a lot of text data)

my hypothesis is that, once a good notation has been written, patterns will emerge extremely quickly from primary sources, that won’t be apparent through purely qualitative analysis

Cabello’s Scenes (1960s-1970s)

NEW YORK CITY

THE FACTORY/WARHOL CIRCLE (1962-1968)

Key Figures: Andy Warhol, Edie Sedgwick, Lou Reed, Gerard Malanga, Ultra Violet
Locations: Factory studios (231 E 47th St), Max’s Kansas City, various Manhattan venues
Primary Sources: Warhol diaries, Factory magazine, participant memoirs
Key Collections: “The Andy Warhol Diaries” (1989), “POPism” by Warhol/Hackett (1980)

TRUMAN CAPOTE’S SOCIAL CIRCLE (1950s-1970s)

Key Figures: Truman Capote, Babe Paley, Gloria Guinness, Lee Radziwill, Harper Lee
Locations: Upper East Side salons, The Plaza, various Manhattan society venues
Notable Event: Black and White Ball (Plaza Hotel, November 28, 1966)
Primary Sources: Capote letters, “Answered Prayers” excerpts, society journalism
Key Collections: “Too Brief a Treat: Letters of Truman Capote” (2004)

SAN FRANCISCO BAY AREA

SF RENAISSANCE/PSYCHEDELIC SCENE (1955-1975)

Key Collections: Snyder-Kyger letters, di Prima autobiographies
Key Figures: Gary Snyder, Joanne Kyger, Michael McClure, Diane di Prima, Ken Kesey, Tim Leary
Locations: North Beach, City Lights Bookstore, Haight-Ashbury
Primary Sources: Beat correspondence, literary magazines, scene memoirs

BERKELEY FREE SPEECH/ACADEMIC CIRCLE (1960s-1970s)

Key Figures: Mario Savio, Richard Dawkins, Ted Kaczynski, Hunter S. Thompson
Locations: UC Berkeley campus, Telegraph Avenue, various Berkeley venues
Primary Sources: FSM documentation, academic correspondence, HST journalism
Key Collections: FSM archives, Dawkins correspondence, HST letters

implementation

mailing list
discord server
blog posts

the combobulator

things where the “combobulator” can be used

get the wives of important figures to spill secrets that their husband tells them on wine night

knowledge

we introduce three symbols: plus + for positive associations, slash / for neutral associations, and dash/minus - for negative associations. we call these sentiment annotators

when a sentiment annotator is in between two people (e.g. $A+B$ ), it is assumed that the relationship is bidirectional. if the relationship is one directional, than a single angle bracket <, > next to the sign is used to indicate directionality.

$B+>A$ reads “B likes A”

$A+>B$ reads “A likes B”

epistemic logic

it is possible that two people like eachother but don’t know the other likes them, orr iso knows allo likes them, but allo doesn’t know iso likes them. this becomes important in the construction of self-reinforcing social structures (“granules” as they are called later in the text). we bring in concepts from epistemic logic.

Knowledge and belief are represented via the modal operators K and B, often with a subscript indicating the agent that holds the attitude. Formulas Kaφ and Baφ are then read “agent a knows that phi” and “agent a believes that phi”, respectively.

: Epistemic Logic, Stanford Encyclopedia of Philosophy

$K_A (B+>A)$ reads “A knows B likes A”

$K_B (A+>B)$ reads “B knows A likes B”

$K_X (Y +>X) : X, Y \in (A, B)$ reads “a and b like eachother, and a and b knows that the other likes them”

by default, when we write $A+B$ , we mean the above statement.

if three or more people have the same sentiment to eachother, than we denote that with set notation followed by the sentiment sign.

$\{A,B,C\}+$ reads “A, B, and C like eachother”.

this notation does not imply knowledge.

in other circumstances, the colon : reads “knows that”.

the pipe | means that something has to happen before something else happens.

the semicolon ; separates inline statements.

gestalts and granules

when everyone likes eachother but does not know that everyone likes eachother, that is called a gestalt. it takes its name from the German word for “shape”. it is denoted with lowercase letter $\gamma$

Example:

$\gamma_{ABC} = \{A,B,C\}+$

a granule is when there are three or more people who all like eachother and everyone knows everyone else likes eachother. these units are indispensable for understanding social interactions. it is denoted with capital letter $\Gamma$

Example:

$\Gamma_{ABC} = \forall \{A,B,C\}:\{A,B,C\}+$

does a granule have an immune system?

tertiary granule

joining

B+C

$\gamma_{A,B,C}$

A:B+C

$\forall$ {B,C}~: $\forall$ {B,C}+>A // neither B nor C knows the other likes A

$\forall$ {C,B}: $\forall$ {C,B}+>A // this is the catalyst and it has to independently of A’s direct involvement (either through B and C finding out through eachother, or one of {B,C} having a notable interaction with A that the other observes)

/* this does not consider the knowledge of a liking the others */

A:( $\forall$ {C,B}: $\forall$ {C,B}+>A) // this has to happen as well. there can be a scenario where A does something defensive that would undo the above step but that is not very common. this reads, “a knows that c and b know eachother likes a”

$\Gamma_{ABC}$ // this is the final granule

synthesizing

A+B;A+C

B+C // could either meet through mutual link or by chance

$\forall$ {B,C}:A+ $\forall$ {B,C} // if a introduces b and c, than this is a given; the gestalt symbol isn’t used here because it has B+C, which isn’t necessary information here

A:B+C // but not for this - a could introduce b and c but b and c might not like eachother, and a doesn’t know for sure or not

$\Gamma_{ABC}$ // this is the final granule

now the amount of connections that need to be broken are 3 instead of one for group dissolution. this is a terniary-granule

tetrary granule

existing granule + infiltrator

$\Gamma_{BCD}$ ; A+{B,C,D}

A:{B+C, C+D, B+D} // not sure if to refer to the granule or the individual relationships.

$\forall$ {B,C,D}: $\forall$ {B,C,D}+>A

A:{B,C,D}+>A

$\gamma_{ABCD}$

two pairs merge

A+B; C+D // initial pairs

A+C; B+D // cross connections

$\forall$ {A,B}:C+D // each of a and b know that c and d like eachother

A:(B:C+D) // a knows b knows c and d like eachother

B:(A:C+D) // b knows a knows c and d like eachother

$\forall$ {A,B}:( $\forall$ {A,B}:C+D) // a and b both know c likes d, and they both know the other knows

$\forall$ {C,D}:A+B

C:(D:A+B)

D:(C:A+B)

$\forall$ {C,D}:( $\forall$ {C,D}:A+B)

B+C; A+D // final connections, these have to happen at a catalyst event

$\gamma_{ABCD}$

this epistemic knowledge could also be used for secret sharing (a knows b knows cs secret, b knows a knows c’s secret, now the secret becomes a topic of conversation between a and b)

sequential triangle building

$\gamma_{ABC}$ exists

D+A; D+B; D+C (D connects to all)

$\forall$ {A,B,C}:D+> $\forall$ {A,B,C}

D:{A,B,C} know each other

$\gamma_{ABC}$ → $\gamma_{ABCD}$

double triangle fusion

$\gamma_{ABC}$ exists; $\gamma_{ACD}$ exists

(A is the bridge node)

B~:D+>A initially

C:{B,D} both connect to A

B+D forms (catalyst moment)

$\gamma_{ABC}$ ∪ $\gamma_{ACD}$ → $\gamma_{ABCD}$

% Krackhardt’s “cognitive social structures”

% Friedkin’s work on social influence networks

epistemic game theory

% Bearman & Moody’s work on network dynamics,