Python script used to generate `organizations.json` (https://gist.github.com/englehardt/a8ce765e410615de83bb40533b0eed29).

merge_org_lists.py

from collections import defaultdict
import json
import dill
import os

DATA_DIR = './'
WEBXRAY_LIST = 'webxray_orgs.json'
DISCONNECT_LIST = 'disconnect_list.json'
OUT_LIST = 'merged_organizations.dill'

# This list maps org keys disconnect:webxray
# webxrays names are preferred as they seem much more updated
# most of this mapping generated automatically by merging orgs that shared
# domains between the list. I spot checked many but not all to ensure an
# actual merge/rebrand occured, but bugs are possible.
MAPPING = {
    'safecount':'kantar',
    'exponential interactive':'tribal fusion',
    'exponential interactive':'exponential advertising intelligence',
    'krux':'krux digital',
    'shopzilla':'the e.w. scripps company',
    'amazon.com':'amazon',
    'tubemogul':'tube mogul',
    'brighttag':'signal',
    '33across':'33 across',
    'contextweb':'pulsepoint',
    'datran media':'pulsepoint',
    'liveinternet':'yadro',
    'maxpoint':'maxpoint interactive',
    'adsafe media':'integral ad science',
    'glam media':'mode media',
    'ibm':'international business machines corporation (ibm)',
    'radiumone':'radium one',
    '[x+1]':'x+1',
    'cbs interactive':'cbs corporation',
    'audiencescience':'audience science',
    'horyzon media':'smart ad server',
    'linezing':'alibaba cloud computing ltd.',
    'cnzz':'alibaba cloud computing ltd.',
    'rapleaf':'liveramp, inc.',
    'webtrends':'netiq',
    'chango':'chango, inc.',
    'dg':'extreme reach',
    'sharethis':'share this',
    'rocket fuel':'rocketfuel',
    'burst media':'blinkx',
    'neustar':'neustar, inc.',
    'ak':'neustar, inc.',
    'mediamath':'media math',
    'm6d':'dstillery',
    'videology':'videology group',
    'insightexpress':'insight express',
    'teads.tv':'teads',
    'spotxchange':'spot x change',
    'cox digital solutions':'coxreps',
    'turn':'turn, inc.',
    'dg':'sizmek',
    'sitescout':'centro',
    'bloom digital platforms':'adgear technologies',
    'vizu':'nielsen online',
    'nielsen':'nielsen online',
    'mochila':'inform',
    'ndn':'inform',
    'doubleverify':'double verify',
    'magnetic':'magnetic media online',
    'cognitive match':'magnetic media online',
    'mybuys':'magnetic media online',
    'fox one stop media':'rubicon project',
    'switch':'switch concepts'
}

# Import and parse disconnect list
d_orgs = defaultdict(set)
disconnect = json.load(open(os.path.join(DATA_DIR,DISCONNECT_LIST), 'r'))
for l in ['Content','Analytics','Social','Advertising']:
    for row in disconnect['categories'][l]:
        for org, info in row.items():
            for url, domains in info.items():
                d_orgs[org.lower()] = d_orgs[org.lower()].union(set(domains))

# The webxray list
webxray = json.load(open(os.path.join(DATA_DIR,WEBXRAY_LIST), 'r'))
w_orgs = defaultdict(set)
for row in webxray:
    org = row['organization'].lower()
    domains = row['domains']
    w_orgs[org] = w_orgs[org].union(set(domains))


# Check for overlap in keys
print "Checking for overlap in domains between lists"
diff = set(w_orgs.keys()).difference(set(d_orgs.keys())).difference(set(MAPPING.values()))
matches = dict()
for key in diff:
    if key in MAPPING.values():
        continue
    for org, domains in d_orgs.items():
        if len(domains.intersection(w_orgs[key])) > 0:
            print "Likely Match! '%s':'%s'" % (org, key)
            matches[key] = org

# Merge the lists
merged = w_orgs
for org, domains in d_orgs.items():
    if merged.has_key(org):
        merged[org] = merged[org].union(domains)
    elif MAPPING.has_key(org):
        merged[MAPPING[org]] = merged[MAPPING[org]].union(domains)
    else:
        merged[org] = domains

# Manual removal of bad mappings
merged['facebook'].remove('akamaihd.net') #Akamai is a cdn for Facebook
merged['exponential advertising intelligence'].remove('tribalfusion.com') # Not same company?
merged.pop('liverail') # now owned by facebook (already included)
merged['conversant media'] = merged['conversant media'].union(merged['valueclick']) # valueclick is now conversant media
merged.pop('valueclick')
merged['alibaba cloud computing ltd.'].remove('360buyimg.com') # not really alibaba (domain might point to them)
merged['alibaba cloud computing ltd.'].remove('ykimg.com') # not alibaba (domain might point to them)
merged.pop('adometry') # subsumed (and owned) by google
merged['sizmek'].remove('dgit.com') # DG was parent company that sizmek spun off from. rest of DB bought by extreme reach
merged['aol'] = merged['aol'].union(merged['adtech']) #adtech owned by AOL
merged.pop('adtech')
merged.pop('buzzcity') # subsumed (and part of) `bv! media`
merged.pop('anquan') # appears to be same company as knownsec
merged.pop('visual revenue') # acquired by outbrain (domain already in list)
merged.pop('vertical acuity') # acquired by outbrain (domain already in list)
merged.pop('convertro') # acquired by AOL (domain already in list)
merged.pop('gravity') # acquired by AOL (domain already in list)
merged.pop('adap.tv') # acquired by AOL (domain already in list)
merged.pop('emar box') # included twice
merged['quisma'] = merged['quisma'].union(merged['i-behavior']) # seem to be same company
merged.pop('i-behavior')
merged['matomy'] = merged['matomy'].union(merged['matomy market']) # same company
merged.pop('matomy market')
merged['iac'] = merged['iac'].union(merged['vimeo']) # vimeo is an iac brand
merged.pop('vimeo')
merged['iac'] = merged['iac'].union(merged['match.com']) # match.com is an iac brand
merged.pop('match.com')
merged.pop('brightroll') # owned (and subsumed) by yahoo
merged.pop('tumblr') # owned (and subsumed) by yahoo
merged.pop('legolas media') # owned (and subsumed) by undertone
merged.pop('vcmedia') # they are admicro
merged['prime visibility'] = merged['prime visibility'].union(merged['adon network']) # adOn acquired by PV
merged.pop('adon network')
merged.pop('bizo') # bizo is linkedin -- now killed off
merged['oracle'] = merged['oracle'].union(merged['bluekai']) # bluekai bought by oracle
merged.pop('bluekai')
merged['oracle'] = merged['oracle'].union(merged['addthis']) # addthis bought by oracle
merged.pop('addthis')

# Print domains mapped to multple orgs (bad mappings)
# Should be none if the above list is comprehensive
print "Checking for domains mapped to multiple orgs..."
for org, domains in merged.iteritems():
    for org2, domains2 in merged.iteritems():
        if org == org2:
            continue
        if len(domains.intersection(domains2)) > 0:
            print "\n\nOrg1: %s" % org
            print domains
            print "Org2: %s" % org2
            print domains2
            print "SHARED DOMAINS"
            print domains.intersection(domains2)

dill.dump(merged, open(os.path.join(DATA_DIR,OUT_LIST), 'w'))