Social graphs of FCC lobbying

The evolution of lobbying coalitionsCo-filing behavior in FCC docket 01-92 on Inter-carrier Compensation
Work in progress, 9/30/2009
Pierre de Vries, Economic Policy Research CenterUniversity of Washington, Seattle

Acknowledgements
Bill Cline and ElhadjiSy (FCC), for providing the underlying public data in a usable form
Marc Smith and Tony Capone, for developing and supporting the NodeXL visualization tool
Jonathan Banks and Anthony Jones (USTelecom), for help in extracting the “et al.” data, and Risa Pavia (UW) for help in creating the fix list

Conclusions
Graph-theory clusters representreal-world alliances
Tracking the evolution of clusters can reveal shifts in alliances
Improving ECFS interfaces and data quality will improve public knowledge of lobbying activity

Co-filing Analysis
Metadata from FCC ECFS database, FCC docket 01-92, April 2001 –December 2008
2,9015 filings, 756 unique filers
Subsidiaries and “doing business as” entities are usually grouped together
e.g. Cable and Wireless plc, Cable & Wireless, Cable and Wireless USA, Cable & Wireless North America.
But for some large players, kept parts separate, e.g. Verizon and Verizon Wireless; AT&T and AT&T Wireless
Sub-set of FCC docket 01-92 where two or more entities file together
Entities that only filed on their own are not shown
Used either metadata given as multiple entity names, or extracted entities from filed documents where “et al.” or “filed on behalf of” given in metadata
Trade associations and coalitions have not been unpacked into their constituents
Sometimes distorts data, e.g. AT&T is represented both on its own account and hidden within the “Missoula Plan Supporters” node
Coalitions unpacked: Oregon Rural LECs, Five State Regulatory Commissions, Coalition for Rational Universal Service and Intercarrier Reform
Companyname changes on acquisition/merger not accounted for:
Frontier Communications Corporation was formerly known as Citizens Communications Corporation
Don’t distinguish between “old” and “new” AT&T, or Verizon before and after MCI merge

Filing intensity varies over time
FNPRM issued 11/5/08
Responses (10/25/2006) to FCC PN (issued 7/25/06) on Missoula Plan (filed 6/24/06)
FNPRM comments (5/23/05)
FNPRM reply comments (10/20/05)
NPRM comments (8/21/01)
Reply comments (11/05/01)
Responses (10/18/02) to T-Mo et al Petition for Declaratory Ruling (filed 9/6/02)

Links between 01-92 and other dockets
Petition of AT&T for interim declaratory ruling and limited waivers pleading cycle established
IMPLEMENTATION OF THE LOCAL COMPETITION PROVISIONS IN THE TELECOMMUNICATIONS ACT OF 1996
In the Matter of Establishing Just and Reasonable Rates for Local Exchange Carriers
FEDERAL-STATE JOINT BOARD ON UNIVERSAL SERVICE
In the Matter of Universal Service Contribution Methodology Federal-State Joint Board on Universal Service 1998 Biennial Regulatory Review
ACCESS CHARGE REFORM
In the Matter of Inter-Carrier Compensation for ISP-Bound Traffic
In the Matter of Federal -State Joint Board on Universal Service High-Cost Universal Service Support
Numbering Resource Optimization
In the Matter of IP-Enabled Services
In the Matter of Lifeline and Link-Up
Request Petition for Declaratory Ruling that AT&T's Phone-to-Phone IP Telephony Services are Exempt from Access Charges
All linked dockets 2001-2008, filtered:
Sub-graphs level 1.5 centered on 01-92 (i.e. all nodes linked to 01-92, and links between them)
edge weight >40 (dockets on either side of the edge were noted together on a filing more than 40 times)
Edge width and color both indicate edge weight: wider/pinker means more joint mentions

Companies typically either always file solo, or always jointly
498 entities always filed alone, e.g. BellSouth, NARUC
152 entities always filed with someone else, e.g. Broadview, Maine PUC
25 entities filed with others in 40%-60% of cases, e.g. tw telecom, Pac-West
Solo filers excluded from co-filing analysis

Links between Filers
If the names of A and filer B both appear on a particular filing…
… they are treated as being linked
Filed on Date 1
Filed on Date 1
A
B
A
B
A
B
The more often they file together…
… the darker the line connecting them (think of the lines being stacked one on another)
Filed on Date 3
Filed on Date 2
A
B
A
B
A
B
A
B
A
B

Different co-filing occurrences…
… lead to a network structure
Filed on Date 1
Filed on Date 3
A
B
A
B
B
A
B
C
C
So far the graphs looked at all filings simultaneously. Looking at a sequence of dates shows different links at different times:
Filed on Date 2
Date 1
Date 3
Date 2
A
B
A
B
A
B
A
B
A
B
C
C
C
C
Deriving a Network Structure

The area of the blob is proportional to the total number of filings made over the whole period (solo or joint)
Additional node attributes (1): Size
AT&T filed many times (big blob), whereas PointOne filed seldom (small blob).
However, one can see that they’re roughly equally linked to other filers. That means that AT&T filed more often on its own.

The more pink a blob is, the more important the filer is in the network.
The color represents the “eigenvector centrality”. A filer with high eigenvector centrality is connected to many filers who are themselves connected to many others. This “centrality metric” goes beyond simply counting the number of connections a filer has; connections to filers who are themselves highly connected confer more influence that connections to less well connected filers.
Google’s PageRank algorithm is a variant of this metric; a page is considered important if many other important pages link to it.
Additional node attributes (2): Color
New Global Telecom and Verizon have the same influence in this graph (same color), even though Verizon filed more often (bigger blob)
GCI, CompTel, and NCTA filed the same number of times (same size), but CompTel is the more influential (pinker), and GCI less (bluer)
Even though CTIA filed often (big blob) it’s not very influential/connected in this network (blue color)

All co-filings 2001-2008 on inter-carrier comp docket 01-29

Nodes are laid out (by hand) to respect clustering
Clusters calculated using Clauset Newman Moore (2004) algorithm (Wakita & Tsurumi 2007 optimization) to find community structure, gathering vertices into groups such that there is a higher density of connections within groups than between them

A Time Series
Underlying data set has day-by-day granularity; these snapshots are integrated over much longer periods

2001-2002
CLEC reply comments to NPRM
T-Mobile et al petition for declaratory ruling

2003-2004
CLECs’ “Cost-Based Intercarrier Compensation Coalition” (CBICC)
Intercarrier Compensation Forum, filed ICF Plan 5 Oct 2004
“Indep. Wireless Carriers”: T-Mobile, W Wireless, Dobson
“CMRS Petitioners”: T-Mobile, W Wireless, Nextel

2005 – summer 2006
CLECs
Major CLECs – FNPRM comments & replies
CLECs, some eventually merging e.g. Lightship, CTC, Conversent; and Xspedius & tw telecom
Rural LECs and their associations

Fall 2006 – end 2007
Missoula Plan Allies
Missoula Plan Opponents:
Mix of CLECs, ILECs and Indep. Wireless
Oregon Rural LECs, supporting Missoula Plan

Jan – July 2008
The calm before the storm

Aug/Sep 2008
ILEC/IXC coalition: Ex parte advocating federalizing VOIP, uniform comp rate for all traffic
CLECs opposing
Verizon’s September 12 proposal, incl. uniform rate

Oct 2008
Five State regulatory commissions objecting to “eleventh hour filings”
Small ILECs trying to slow down process
Broadening CLEC coalition opposing change towards flat rate
Mid-size rural LECs opposing flat rate comp, supporting status quo
OPASTCO/WTA Plan

Nov/Dec 2008
“Coalition for Rational Universal Service and Intercarrier Reform” – urban & rural CLECs
Opposition to AT&T/IXC “self-help” from small LEC and conf-call players
Rural cellular – note they’re closer to the CLECs than the RLECs

Summary of Coalition Patterns
Opponents are connected: ILECs, CLECs, and cellular
Rural LECs and their associations keep to themselves

Top 20 Impact Depends on Chosen Metric
CLECs not only band together, but also file a lot, and often.
NTCA carries the water for RLECs
* Filers that appear in three or more columns are color coded

Observations
Graph clusters seem to correspond to real-world interests
A large number of filings form one large connected graph (the blob in the center)
It’s connected in aggregate over the whole time series: shifting alliances
In the course of the proceeding, one can find a link between opposing parties e.g. a proponent of the “Missoula Plan” like AT&T is linked to an opponent like XO via both of them co-filing with the CTIA at different dates (“Six Degrees of Kevin Bacon”)
There are many parties that only co-file once or twice
Most of them are pairs
There are a few large groups of co-filers that show up only once in the record, and aren’t seen before or after
Frequent Filers are usually different from Cross-Connectors
Frequent filers like AT&T, CTIA and NTCA don’t often file in coalition
Connectors that bridge alliances (e.g. Hypercube, iBasis) don’t file all that often
Some fall in both groups, e.g. XO and Cavalier

Value of the approach
Insiders can use graphs to identify:
detailed trends at a glance
potential collaborators or defectors, e.g. by looking for coalition members who are bridges between groups, or peripheral
Outsiders can grasp the overall structure of a proceeding without having to read the entire record
News organizations can use:
cluster evolution to show changes in coalitions
network structure to guide understanding of search results

Implications for FCC
Poor quality of information input by filers impedes transparency
Endless misspellings of company names
Not all entities involved in a filing are listed
Filers make mistakes (e.g. mistyping docket number) but can’t remove mistakes; they simply file again
Require more information in metadata
Require all entities names to appear in the Filed on Behalf Of field, i.e. “et al.” not allowed
Distinguish between ex parte letters and meetings
Use standard web techniques to facilitate data input and retrieval
Require log-in with company ID when submitting data to ECFS
Require filer name to be registered; subsequently metadata can only be chosen from pre-registered information, not added de novo
Offer drop-downs and auto-complete to add co-filers
Provide web interfaces for downloading data in bulk, and as daily feeds
Improve systems for correcting errors
Allow filers to remove incorrect data (only filer can remove what was filed)
Penalize errors, e.g. by naming and shaming
Invest in cleaning up old data: requires public/private effort?

Caveats
Graph depends on metadata entered into ECFS by filers, which can be unreliable
misspellings (e.g. ATT for AT&T)
inaccuracy (e.g. a filing attributed to AT&T was actually on behalf of a number of companies, and so is not counted as a co-filing)
ambiguity (e.g. there are many companies whose name includes “Citizens”, and they all seem to be different)

Some Bad Data Examples
BellSouth:
BellSouth Coration
BellSouth Corpm
BellSouth Corps
BellSouth D.C.
BellSouth TELECOMMUN
BellSouth TELECOMMUNIC
BellSouth TELECOMMUNICA
BellSouth TELECOMMUNICAT
BellSouth TELECOMMUNICATI
BellSouth Telecommunication
BellSouth Cellular CORPOR
Misspellings of “Communications”:
Comminication
Commnications
Communictions
Commuications
Commuincations
Communcations
COMMUNIATIONS
Communicaitions
COMMUNICAITONS
Communicatiions
Communicatins
Communicationas
Communicationsn
COMMUNICCATIONS
Communictions
Communocations
Comunications
Coommunications
Cummunications
California PUC:
CALIFORNIA PUBLIC UTILIL
CALIFORNIA PUBLIC UTILIT
CALIFORNIA PUBLIC UTILITE
California Public Utilites Commission
CALIFORNIA PUBLIC UTILITI
California Public Utilities
CALIFORNIA PUBLIC UTILITIES COMMISSION
California Public Utilities Commission - 99-204
California Public Utilities Commission and People of the State of California
California Public Utiltiies Commission
Calilfornia Public Utilities Commission
Commissioners Lynch and Wood, California Public Utilities Commission
People for the State of California and Ca. Public Utilities Commission
People for the State of California and Cal. Public Utilities Commission
People for the State of California and California Public Utilities Commission
People of the State of California & Public Utilities Commission
People of the State of California and Cal. Public Utilities Commission
People of the State of California and California
People of the State of California and California Public Utilities Commission
People of the State of California and Public Utilities Commission
People of the State of California and the Cal Public Utilities Commissoin
People of the State of California and the California Public Utilities Commission
Public Utilities Commission of the State of California
State of California and the California Public Utilities Commission
State of California Public Utilities Commission
The People of the State of California and by proxy for CPUC
The People of the State of California by proxy for CPUC

Caveat (ctd): Coalitions are Understated
Analysis puts a lower bound on connectivity
Some connections are not revealed through co-filing; entities may be linked, e.g. through participation in a trade association, but not file together explicitly
Co-filing is undercounted since we rely on the metadata entered into ECFS. Sometimes just one company name given, even though there multiple companies involved, or a list of company names may not include all filers. (This data can be obtained from the underlying document, but at the price of significantly more effort.)
This analysis deals with only one docket; companies may co-file more frequently on other dockets

Conclusions (restated)
Graph-theory clusters representreal-world alliances
Tracking the evolution of clusters can reveal shifts in alliances
Improving ECFS interfaces and data quality will improve public knowledge of lobbying activity

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Social graphs of FCC lobbying

by Pierre de Vries on Sep 21, 2009

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Social graphs of FCC lobbying — Presentation Transcript