% \maketitle

Would Wikipedia be one of the most visited websites in the world if other online collaborative encyclopedia projects had been more established when it was founded? Or was Wikipedia helped by the fact that its predecessors had engaged and trained hundreds of its future contributors? Do new discussion communities on Reddit compete with existing communities for contributors? Is the evolving world of online communities better understood as a competitive struggle for resources or as symbiotic relationships that support a web of interdependent communities?   
How does the environment of existing online communities shape the growth, performance, and impact of new groups?

Answering these questions requires an \textit{ecological understanding} of online communities that accounts for the complex dynamic interactions between communities and their environments. 
Prior studies of the growth, survival, and success of online communities have focused almost exclusively on communities' internal features \citep{kraut_building_2012} and have largely neglected environmental factors \citep[e.g.,][]{halfaker_rise_2013, kraut_building_2012, schweik_internet_2012, shaw_laboratories_2014, teblunthuis_revisiting_2018}. 
Analyses from this ``focal organization perspective''  \citep{hannan_organizational_1989}    typically account for only a small amount of variation in communities' growth, longevity, and performance. Ecology provides a compelling alternative theoretical approach. In biology and organization studies, ecological approaches have shown that success is largely---and sometimes overwhelming---a function of what others groups are doing \citep{hannan_organizational_1989, worster_natures_1994}.

Ecology is a scientific approach to understanding how interdependence between individuals, collectives, and environments shapes the world \citep{worster_natures_1994}.
%Ecology grew from roots in 18\textsuperscript{th} century naturalism into a science of interrelationships between organisms, between species, and between organisms and the environment \citeh{worster_natures_1994}. 
Although first developed to understand biological ecosystems, ecology's theories and methods influenced the development of human ecology, and later of organizational ecology \citep{hannan_organizational_1989, mcpherson_ecology_1983, park_human_1936}. Organizational ecology is a vast field in social science that explains the success, failure, and evolution of newspapers, microbreweries, social movements, and voluntary organizations \citep{carroll_concentration_1985, carroll_why_2000, mcpherson_ecology_1983, soule_competition_2008}. 
Ecology can provide practical solutions to problems in complex systems like effective wildlife management, pest control, and sustainable utilization of renewable resources. In organization science, it provides compelling explanations for industrial life-cycles, organizational specialization, and patterns of collaborative partnerships.

Recent research in the social computing on interdependence between online communities suggests that ecological analyses can provide not only novel scientific understandings but also viable community management strategies \citep{chandrasekharan_you_2017, kiene_managing_2018, tan_tracing_2018, teblunthuis_density_2017, wang_impact_2013, vincent_examining_2018, zhu_impact_2014}.  For example \citet{chandrasekharan_you_2017} found evidence that banning hateful communities on Reddit decreased hate speech in related communities.
Community outcomes such as growth and survival depend on membership overlaps between communities \citep{wang_impact_2013, zhu_impact_2014}, but the nature of the resulting relationships remains unclear. \citet{wang_impact_2013} found that participant overlaps between Usenet groups were associated with \emph{competition} and decreased participation in both communities. However, \citet{zhu_impact_2014} found evidence that membership overlap between wikis is associated with \emph{mutualism} and benefits for both communities. Such contradictory findings point to the need for deeper, more precise theories of how ecological dynamics play out in online communities. 
% In this sense, ecological approaches sit at the edge of established knowledge in field of social computing.  
% That said, bare novelty itself is not a compelling motivation for a research program.


Online communities are a dynamic, growing, and increasingly important form of organization that enable collaboration on public goods in contrast to the private goods production most studied in organizational ecology \citep{benkler_peer_2015}. 
Through peer production, the Wikipedia community has produced the largest collaborative effort and most important reference work in human history.
Free/libre open source software (FLOSS) communities have produced tens of billions of dollars worth of software made freely available online \citep{benkler_peer_2015}. 
Other online communities like subreddits provide information, social support, and entertainment to millions of people.
Ecological research into online communities may enable us to understand \emph{why} and \emph{how}  of the millions of attempts to build communities, only a tiny percentage of manage to mobilize participants and to sustain collaboration \citep{schweik_internet_2012, hill_studying_2019, shirky_here_2008}.
However, online communities are vastly different from the organizations organizational ecology was developed to study.
Classical hypotheses in organizational ecology are built on a system of interlinked assumptions that were informed by background knowledge of 20\textsuperscript{th} century organizations.  
I argue that past applications of organizational ecology to online communities have not anticipated how this change in context could lead to changes in theoretical predictions. 

%Much less isi undertsoo
Therefore, I do not pick up organizational ecology as an authoritative model or set of laws capable of explaining the growth and decline of online communities. 
Instead I drew some ideas directly from mathematical ecology, a subfield of applied mathematics, to better understand the foundational assumptions of an ecological perspective.
On this foundation, I see this project as building an empirical basis for an ecological theory of online communities that starts by inferring competitive and mutualistic relationships between online communities. 
% Studying these relationships is the place to start both methodologically and conceptually. 
Once ecological dynamics between communities are demonstrated to have measurable relationships with the growth and performance of online communities, we can more fully explain their origins and consequences. 

My empirical studies are framed in terms of how the ecological approach provides new insights and ways of studying interdependent online communities.
However, these studies' methodological designs and empirical results also contribute to organizational ecology by expanding its application beyond the scope of its founding assumptions.
The developers of organizational ecology developed strong intuitions about when organizations will complement or compete with one another based on claims from prior organization theory including that organizations compete over resources, are shaped into established forms by homogenizing pressures, are defined by strong boundaries, and lack capacities for rational adaptation.
Because they typically lacked sufficient longitudinal data to infer when organizations are competitors or mutualists, they have rarely tested these assumptions directly, but rather test theoretical predictions about outcomes like organizational formation, survival, and change \citep{hannan_organizational_1989, baum_ecological_2006}. 
The literature on interdependence between online communities is relatively young and provides less background knowledge that can inform such assumptions, but data from online communities enables a stronger empirical basis for understanding relationships between groups.

Although the time series models in Chapters 2 and 4 depend on fewer assumptions about when competition or mutualism occur compared to the most influential frameworks of organizational ecology, Chapter 2's key finding, that mutualism is more common than competition among online groups with highly overlapping users, radically departs from organizational ecology which has found that both firms and voluntary organizations with highly overlapping resources typically compete \citep{mcpherson_ecology_1983, hannan_organizational_1989}.  Although I initially planned to continue developing model-based approaches to explaining the performance of online communities, to find widespread mutualism was surprising and demanded qualitative validation and explanation in terms of the experiences of online community members.  Therefore, Chapter 3 reports on an interview-based study of members of highly overlapping online communities. It concludes that ``no community can do everything'' because groups of overlapping communities are characterized by high degrees of specialization. Each community seems to provide a different set of benefits. As Chapter 3 discusses, this is consistent with ecological theory which suggests that highly specialized groups with overlapping memberships are unlikely to compete and that groups provide complementary benefits that can ``spill over'' and drive mutualistic dynamics. 

Knowledge from interviewees includes invaluable cases of mutualism, grounded descriptions of relationships between overlapping online communities, a strong sense that Chapter 2's models are right about the ubiquity of mutualism, and clues about the importance of specialization.    However, the interviewees did not provide much to explain processes by which systems of specialized mutualistic overlapping communities develop. In Chapter 4, I draw from strands of organizational ecology that use evolutionary theory as a foundation for processes of change.  In addition, the models from Chapter 2 are effectively the most simple time series models that might be used to infer ecological interactions.  They depend on many assumptions that are probably unrealistic in the setting of online communities.  Therefore, Chapter 4 adopts non-linear time series models developed by mathematical ecologists to study nonlinear dynamics.  These models are important to Chapter 4's study design for investigating change processes and also compel us to conceptualize competition and mutualism interactions that are not static and fixed, but that vary over time. 

% This doesn't quite work yet. Need to develop the insights for organizational ecology.
In sum, online communities are a kind of organization, at least in the sense that organizations are ``constructed as tools for specific kinds of collective action'' \citep{hannan_organizational_1989}. Even when online communities are constructed to facilitate communication with strangers on the internet about a topic, this facilitation depends on the sustained contributions of members to keep the conversation going and structures for regulate behavior to maintain a suitable conversation space \citep{kraut_building_2012}. Online communities bear other similarities to organizations including their use of formalized roles, rules, and procedures and their use of boundaries defining the scope of activity \citep{foote_formation_2019}.

That said, online communities are distinctive in that they are public-good producing voluntary groups constructed through computer-mediated communication. 
Features of online communities depart in important ways from the types of organizations that classical organizational ecology has studied the most.  Online communities (1) are dependent on volunteer participation, (2) allow participation at very low levels of granularity (3) are weakly bounded and (4) face different potential sources of inertia.
The remainder of this chapter discusses the methodological and theoretical implications of these interrelated features for ecological analysis.
% Some of these features are often said to be made possible by the digital media through which online communities are constructed. 
% Drawing on ecological theory and findings from the empirical chapters, I will suggest a role for ecological dynamics in the processes that give rise to and stabilize these structures.

%  

% Online communities (1) produce public rather than private goods and (2) online communities are online.  
\section{Online Communities as Voluntary Organizations}

Ecological theories conceive of dynamics among individuals that share resources needed for production and survival to explain change in the size and composition of groups over time.
Organizational ecology explains macro-level social change in economies and industries through in an ``evolutionary'' style through mechanisms of the selection and adaptation of firms in a changing resource environment \citep{ven_explaining_1995, hannan_organizational_1989}. 
Each organization's survival depends on its \emph{niche} in the resource environment. The notion of a niche is central, if sometimes slippery, and aims to capture the position of an organization in an abstract, high-dimensional resource space \citep{hannan_organizational_1989}.
Organizational ecology was developed mainly to study commercial firms whose survival ultimately depends on their potential to offer returns on investment.
Profitability of these firms typically hinged on expansion to control greater quantities of resources, provide economies of scale and create the potential for monopolistic rents \citep{hannan_organizational_1989}.  
Niches for such organizations are often defined in terms of established categories of organizational forms \citep{carroll_why_2000}, technological production factors \citep{dobrev_dynamics_2001}, or economic outputs \citep{dobrev_shifting_2003}.

How should we define niches for online communities?  
They use the low-cost communication systems of the Internet to coordinate voluntary production of public information goods like encyclopedias, FLOSS programs, and cultural artifacts \citep{benkler_wealth_2006}.
An online community might produce something damaging to the broader society, such as computer viruses or misinformation, but the types of online communities considered here produce public goods defined as \emph{non-excludible} (in principle, an individual cannot be excluded from utilizing them) and \emph{non-rival} (utilization does not diminish the good's value). 
Therefore, the survival of online communities depends not on capacities to generate revenues and capture profits, but on the consistent participation of volunteer members who have heterogeneous motivations for contributing to a public good \citep{lampe_motivations_2010, shah_motivation_2006}.

Dependence on volunteer members is something online communities have in common with voluntary organizations like social clubs, churches, or fraternal organizations \citep{bimber_collective_2012}. 
Voluntary organizations have been studied in organizational ecology by J. Miller McPherson and collaborators who investigate overlapping niches defined by organizational members and associated demographic patterns \citep{mcpherson_evolution_1991, popielarz_edge_1995, mcpherson_ecology_1983, mcpherson_testing_1996}. 
For example, \citet{popielarz_edge_1995} locate voluntary organizations' niches in ``Blau Space''  corresponding to the distribution of their members' demographic characteristics and  explain how voluntary organizations tended to become racially or educationally homogeneous in terms of competitive dynamics over members' time and attention \citep{popielarz_edge_1995}.   Similar to McPherson, ecological studies of online communities, including the present work, have defined niches of online communities in terms of their participants \citep{wang_impact_2012, zhu_impact_2014}. 

However, membership is not the only plausible way to define an online community's niche. As a consequence of their nature as public-good producing voluntary organizations, their survival does not depend on expansion. Although influential models of the growth of online communities have assumed that motivations to participate in online communities increase as communities grow \citep{butler_membership_2001, kraut_building_2012}, recent surveys and interviews find that large and small communities provide different sorts of benefits \citep{hwang_why_2021, foote_starting_2017}. As Chapter 3 finds, larger communities provide steady streams of content and larger potential audiences, but are less capable of providing tight-knit socialization or specialized information.

This kind of size-dependent specialization resembles ``niche-width'' arguments in organizational ecology.  For example, \citet{carroll_concentration_1985}  seeks to explain the coexistence of large and small organizations within an industry by proposing that generalists, who have wide niches, under-perform in certain areas of the resource space.
Smaller organizations can exploit this under performance by specializing in these areas.
However, as \citet{dobrev_dynamics_2001} argue, specialist organizations can grow large in certain circumstances and then organizational size can be uncorrelated with niche width. This is the case with online communities.
For example the subreddit \texttt{r/prequelmemes} is dedicated to making and sharing memes only about the Star Wars and is the largest Star Wars related community on Reddit.
Therefore, it important to recognize that memberships may not capture all the relevant dimensions of an online community's niche.
Indeed, Chapter 3 finds at least three dimensions of specialization in terms of the benefits that members obtain from online communities.
These are (1) access to the largest possible audience, (2) socialization in a homophilous community and (3) ability to find specialized content or information. 

% TODO note on the using topic overlaps in Chapter 4.
Still, for the purposes of the studies in Chapters 2 and 4, membership overlaps provide a number of advantages.  
The benefits of participation may not be easily observed, so measuring online community niches in terms of participation, which is observable, is empirically tractable. 
Furthermore, findings in Chapter 3 suggest that community leaders do not normally seek to appropriate private value from their communities. If so, then it seems more likely that ecological dynamics that shape the growth and survival of online groups will have more to do with participation, the main rival resource on which online communities depend.
Finally, studies in organizational ecology have set out to test models that depend on  linear or curvilinear relationships between niche-overlap and competitive pressures and this required stronger assumptions around the measurement of niche width than those needed here \citep{carroll_concentration_1985, ,dobrev_shifting_2003}.
Chapters 2 and 4 use membership overlaps to identify clusters of highly related communities while time-series models are used to infer competition and mutualism.  These models bear their own assumptions, but the threat to scientific validity moves from the task of measurement to the task of statistical inference.  Chapter 5 discusses how expanding definitions of an online community's niche to account for additional dimensions of specialization will be important for future work.

\section{Openness Allows Dividing Time into Little Chunks}

Although following McPherson's use of membership-based niches makes sense because online communities depend on voluntary contributions to produce public goods, a second key feature of online communities departs from the voluntary organizations in McPherson's studies. This is that online communities provide opportunities for ``tiny acts of participation'' like signing a petition, fixing a typo on Wikipedia, or ``liking'' a post.
When individuals can act in small granular ways they can easily participate in many online communities in rapid succession \citep{benkler_wealth_2006, margetts_political_2015, tan_all_2015}. 
% What are the implications of this change for ecological interactions among online communities?
By contrast, McPherson assumes that organizations conduct their activities in face-to-face in-person meetings and theorizes that constraints of time and space strongly limit the number of organizations to which an individual can belong \citep{mcpherson_ecology_1983}.
After work and other obligations, it seems unlikely that many people would have time to belong to very many voluntary organizations at once, so participation in an organization is highly rival and overlaps in membership are tightly coupled with competition.

Chapter 2 and prior ecological studies of online community participation follow this intuition by considering membership to be a rival resource, and assuming that online communities with overlapping users are those likely to have significant ecological interactions   \citep{butler_membership_2001,wang_impact_2012}. However Chapter 2 avoids assuming that these interactions will be competitive and instead finds that mutualism among highly related online communities is about 4 times as common as competition and in Chapter 3 interviewees described how these related communities have specialized roles. Together, these findings suggest that the growth and survival of a sufficiently established community is not often limited by competition over membership.
Why is membership overlap so strongly associated with competition in the context of in-person voluntary organizations but highly overlapping online communities are often mutualists? 

% On the other hand, online groups also rely on \textit{nonrival} resources. They can even produce connective and communal public goods like opportunities to communicate or collections of information \cite{fulk_connective_1996} which can be ``antirival'' when their usefulness increases as a result of others using them \cite{kubiszewski_production_2010, weber_political_2000}. For example, the usefulness of a communication network increases as more people join it \cite{fulk_connective_1996, katz_network_1985}. Similarly, the usefulness of an information good can increase as more people come to know, refer to, and depend upon it \cite{kubiszewski_production_2010, weber_political_2000}.
% % as when 
% %Awareness that an online group provides an audience can motivate participation  \cite{zhang_group_2011}. 
% If multiple online groups help build the same connective or communal public goods, they may form mutualistic interactions where contributions to one group may ``spill over'' and motivate participation in mutualist groups \cite{zhu_impact_2014}.   
% Ecological approaches seek to understand how different types of resources will limit or promote growth.

% TODO cite aaron swartz

Online communities ``transcend time and space'' using asynchronous and low-cost telecommunications \citep{jarvenpaa_communication_1998, peters_speaking_1999}.  Although individuals are fundamentally constrained in their available time and energy, they can finely divide their time over many communities. \citet{margetts_political_2015} suggest this less ``lumpy'' form of participation helps enable online collective action.  
Similarly, the fine-grained division of individuals' activities across communities is closely related to the success of online communities having ``open'' organizations with minimal barriers to participation. \citeauthor{benkler_wealth_2006} claims that the fact that information is non-rival is central to how online communities successfully peer-produce public information goods.  This characteristic of information goods also enables open organizational structures so that peer-production projects can incorporate contributions from peripheral contributors \citep{benkler_wealth_2006, bryant_becoming_2005}. 
Together, these factors allow levels of participation that are even more unequal than those found in other voluntary organizations. For example, while ``the top 20\% of volunteering individuals contributed 50\% of the time volunteered in the USA'' in 2016, the top 1\% of Wikipedia editors put in 77\% of the effort into editing Wikipedia \citep{matei_structural_2017}.  
% Such inequalities in the degrees of participation in an online community have often been conceptualized as a division between ``core'' and ``peripheral'' members. 

% TODO add citations
When people can spread their time across many open communities, this also shapes the nature of membership in a community and the boundaries between communities.
Organizational ecology was developed with the relatively impermeable boundaries of commercial organizations in mind \citep{hannan_organizational_1989}. 
This is a second reason why \citeauthor{mcpherson_ecology_1983}'s studies of voluntary organizations provide a good model for studying ecology of online communities. 
While commercial firms have relatively strong boundaries around internal activities and control over much of their employees time, voluntary organizations open up more of their activities to outsiders in order to attract participants.
As noted above, \citeauthor{mcpherson_ecology_1983} assumes that voluntary organizations with overlapping niches will compete.
However,  mathematical ecology shows that niche overlaps do not necessarily imply competition in complex systems involving multiple organizations or resource dimensions because factors other than the overlapping resources can limit growth \citep{armstrong_competitive_1980}. 
%  and more often because of internal limitations of the community's ability to provide benefits to its membership.


% TODO cite some stuff about 
Finally, by modeling community size as the ``tiny act of participation'' of commenting in a given week, the analysis of ecological dynamics in Chapters 2 and 4 might be predisposed to find mutualism. Although quantifying time spent on contributions might not be possible in the case of Reddit (how would we count the time someone spends creating art to share with an online community?), it is possible that a study of participation intensity might find weaker mutualism and stronger competition if small contributions from  peripheral members are less rival than larger contributions from core members.
On the other hand, if these contributions take the form of non-rival information goods, then communities will be unlikely to compete over them (an artist is likely to share their effortful creations with all communities from which they desire an audience).    
The findings of Chapters 2 and 3 both suggest that part of why subreddits with overlapping memberships can provide complementary benefits and form mutualistic ecological relationships is that membership in multiple online communities is relatively inexpensive. If subreddits became closed organizations, perhaps by introducing pricey membership fees, one would expect stronger competition over membership. In this way, openness appears to provide conditions less conducive to competition and more conducive to mutualism.

% Stuff about organizational boundaries here

\section{How Should Online Communities be Divided into Organizational Forms?}

Related to openness and the predominance of mutualism is Chapter 3's finding of extensive specialization among online communities that have similar topics and similar members. One rarely observes more than one active subreddit with similar topics that is not differentiated in some significant way, often in size, rules or topic.  Groups of related online communities thus depart from the organizational forms studied in organizational ecology in ways that trouble the specific strands of organization ecology used by prior research on online communities. 

% As described in Chapter 2, early studies of competition and mutualism online communities adopted density dependence theory, perhaps because it is the most influential theory in organizational ecology.  Population ecology is a set of theories and models for analyzing competition and mutualism among a set of groups that are assumed to be very similar to one another. Community ecology on the other hand studies relationships between groups without assuming they are similar. 

Chapter 2 defines its approach as community ecology because it focuses on relationships between different online communities.
This may surprise readers of the organizational ecology literature in sociology which defines community ecology as the study interactions between populations of organizations, but I argue it is reasonable given the heterogeneity of overlapping online communities.  
I will also note that studies in Communication have applied the community ecology approach to study competition and mutualism between telecommunication companies \citep{dimmick_theory_1984, barnett_competition_1987} or networks of organizational relationships \citep{dimmick_theory_1984, margolin_normative_2012}.  However, such studies are a small minority in the literature. 

\citet{aldrich_organizations_2006}, \citet{hannan_organizational_1989}, and \citet{astley_two_1985} all consider community ecology as having a distinct level of analysis from population ecology.
They use levels of abstraction analogous to those used in biological ecology where a population is set of individual organisms of the same species and a community is a set of interacting populations.  
For these organizational ecologists, a population is a set of organizations having the same \emph{organizational form} and a community corresponds to an \emph{organizational field} of related organizational forms. 

The identification of an organizational form is of central importance. 
Both organizational and mathematical ecologists are aware that population ecology models like density dependence depend on the assumption that the population under study is homogeneous in the sense all members of the population are equally subject to the same intra-population mutualistic and competitive forces.
Organizational ecologists have justified these assumptions by carefully demarcating different types of organizations into organizational forms theorizing that discrete boundaries around organizational forms are constructed by homogenizing features like efficient ways to bundle transactions \citep{williamson_economics_1981}, external regulatory frameworks, or other mechanisms of institutional isomorphism \citep{dimaggio_iron_1983,hannan_organizational_1989}.
Still, the definition of organizational forms in organizational ecology often amounts to accepting an established categorization. The fascinating question of how the processes by which such categorizations are socially constructed are related to the ecological dynamics within and between organizational forms has driven much work by Hannan and his collaborators in recent years \citep{pontikes_ecology_2014, hannan_logics_2007, hannan_concepts_2019}. 

Although McPherson's series of papers on the ecology of voluntary organizations may best be described as a community ecology analysis of categories of voluntary organizations like ``sports'' or ``youth serving'' organizations, at times he resists analogizing organizations as biological populations:
\blockquote[\cite{mcpherson_ecology_1983}]{A population of organizations, then, is not a set of discrete creatures who must mate with each other to reproduce, but a froth of bubbles, constantly sharing or exchanging members, growing and dying, and being absorbed and segmented in response to changing conditions}.
In this instance as well as others, McPherson's papers sometimes slip from discussing ecological dynamics among different organizational forms, which is measured in the data, and between different organizations, which is not. In the above quote, McPherson clearly has a dynamic ecosystem of differentiated organizations in mind. Perhaps the set of ``sports'' organizations contains too much heterogeneity to constitute an organizational form.

Later organizational ecologists studied diversity within an organizational population by appealing to a distinction between  ``core'' features which define the organizational form and are mostly stable over time and ``peripheral'' features which are allowed to vary \citep{hannan_organizational_1989}. Organizational ecologists have studied how variation and specialization of peripheral features shapes competition within an organizational form. For example, \citet{dobrev_shifting_2003} studies how degrees of overlap among automotive firms' technological niches, measured as engine horsepower, changed over time and affected organizational survival. Similarly, Chapter 2 and prior ecological studies of online communities measure user overlap density to quantify how much a community's members participate in other communities \citep{zhu_impact_2014, zhu_selecting_2014, wang_impact_2012}.  Chapter 4 takes this a step further by studying how dynamically shifting niches are related to competitive and mutualistic interactions.

Organizational forms of online communities might be defined according to the platform hosting them.
Indeed, prior ecological studies of online communities have done exactly this and treated sets of communities sharing a platform like Usenet or Wikia as a population.
However,  technological boundaries around platforms may not ensure sufficient homogeneity to justify treating these sets of communities as an organizational form.
One finds enormous diversity in the topics and purposes of communities upon exploring a platform like Reddit, Facebook Groups, or Wikia.
Chapter 3 finds that, even when topics and memberships are very similar, online communities are specialized in other dimensions. Although a platform clearly provides a set of common technological affordances, many platforms are flexible enough to allow a great deal of diversity in scopes, rules, and communities can greatly expand available affordances by using auxiliary technologies like bots \citep{kiene_technological_2019}.
It is thus questionable that overlapping features of online communities like memberships or topics are ``peripheral'' while the use of a platform is ``core'' and therefore it is difficult to identify populations of online communities \emph{a priori}.

% Although Chapter 2 is framed as introducing a novel community ecology approach to social computing that is complementary to population ecology, these theoretical arguments suggest that defining  may not be very useful when applied to online communities. 

When categorizations of organizations of interest are not well-understood, \citet{hannan_organizational_1989} recommend using numerical clustering to find divisions of organizational forms.
The quantitative analyses in Chapters 2 and 4 are all based on a clustering algorithm that groups subreddits with similar kinds of users.
I define these as ``ecological communities'' in a way that is consistent with the sense of Aldrich and Reuf, although they  are interested in competition and mutualism between organizational forms. 
However, as Chapter 3 demonstrates, this results not in clusters of online communities having similar forms, but in groups of subreddits whose topics are related but whose forms vary along dimensions of scope, size, and internal structures like rules.
Population ecology is designed to study the mutualistic and competitive processes among members of an organizational form.
Community ecology is designed to study mutualism and competition between populations of organizations having different forms.
Neither theory seems to fit exactly with subreddits, but Chapter 2 can be understood as advancing a community ecology analysis of organizational forms assumed to have a single member organization. If this seems overly nuanced, one can simply adopt the framing of Chapter 2 and ignore matters of organizational forms and fields and treat community ecology as a relational framework and population ecology as an environmental framework.

% as a study of ecological interactions within clusters of online communities. 

% In contrast to Hannan and Freeman's approach, the inspiration for prior ecological research in online communities \citep{wang_impact_2012, zhu_impact_2014},  

% describes a \emph{selection} process in which many online communities are created but fail to sustain participation if they do not find a sufficient niche.   

\section{Inertia and Adaptation}

Organizational ecologists have tended to emphasize selection processes because  organizational cores appear to change relatively little.  External homogenizing forces described and by internal factors like culture and routines that are difficult to change lead to ``structural inertia.''  Structural inertia limits an organization's ability to rationally adapt to a changing environment.   Organizations typically lack sufficient information about their environments and the ability to coordinate change with sufficient precision in order to rationally adapt, especially when it comes to change in the ``core'' aspects of an organization \citep{hannan_structural_1984}.  However, they also experience exceptional transformational periods that accompany an increased risk of failure \citep{aldrich_organizations_2006}.  
If organizations are adaptive, then a teleological or functionalist explanation of organizational change may be better than an ecological one \citep{ven_explaining_1995} and theories of change in organizational fields should be based on Lamarkian adaptation-based evolution instead of Darwinian selection.

Whether online communities can adapt has important consequences for design interventions aimed at improving the quality or safety of online spaces. Adaptive online communities may adopt new tools for moderation or quality control or implement policy changes to address newly uncovered problems. But online communities having substantial structural inertia will struggle to adapt, problems that go unaddressed will contribute to communities' declines, and solutions will largely emerge through the construction of new communities.  A selection-based change process may be slower than an adaptive one because it will be limited by rates of community formation and decline. 

% Three possible types of explanations: leadership, membership composition, routinization! 
Prior research into online communities suggests a relatively high degree of structural inertia, at least when it comes to policy \citep{teblunthuis_revisiting_2018, halfaker_rise_2013}, but the origins of this inertia are not obvious. 
One explanation looks to the composition of contributors to an online community and sees social barriers to diverse newcomers as limiting capacities for change \citep{lam_wp:clubhouse?:_2011, tripodi_ms_2021,menking_people_2019}.
Another explanation is the entrenchment of oligarchical leadership \citep{shaw_laboratories_2014}, who may be conservative and resist change.
Yet in classical organizations, leaders often seek purposeful adaptation, but are foiled by internal sources of inertia like organizational cultural, internal patronage networks, conflicts among stakeholders, and routines \citep{hannan_structural_1984, ven_explaining_1995}.  Some of these inertial forces appear to have analogs in online communities such as the stability of emergent roles \citep{arazy_how_2017, arazy_functional_2015}, routines \citep{keegan_analyzing_2016}, and internal conflict that may stabilize policy \citep{shi_wisdom_2019}. 

Chapter 4 explore the relationship between ecological dynamics and adaptive processes in online communities by relaxing assumptions of the model in Chapter 2 to allow ecological interactions between online communities vary over time. This allows us to explain that mutualism is more common than competition in Chapter 2 because periods of mutualistic interaction last longer than periods of competitive interaction. Finding that competitive and mutualistic dynamics in online communities are not static, but dynamic and vary over time sets up hypotheses tests about how online communities might adapt to avoid competition or increase mutualism. While I find evidence that communities increase their specialization by decreasing their user and topic overlaps in competitive conditions, I do not find that this decreases competition and increases mutualism.
This suggests that variations in competitive and mutualistic dynamics are driven by exogenous events and that at least when it comes to positioning themselves with respect to one another, that successful online communities have ``selected an effective niche'' \citep{zhu_selecting_2014}.  
As discussed further in Chapter 5, the evidence from Chapters 4 does not support strong claims about whether mutualism is common because of adaptation or selection. Future work should seek to demonstrate the selection process in action.  


%Given that they vary over time, if online communities act rationally to position themselves relative to each other in ways that optimize their mutualism, we might find temporal correlations between a communities changes topic and membership overlap and its competitive and mutualistic relationships.

%If not,

\section{Conclusion: Contributions to Organizational Ecology}

Organizational ecology began by asking ``Why are there so many kinds of organizations?'' \citep{hannan_organizational_1989, hannan_population_1977}. It provides a conceptual model of how people build systems of interdependent social structures within organizational fields, and a vast and rich literature that was initially developed to study firms in long-running commercial industries. Although \citet{hannan_organizational_1989} account for the demography of industrial unions in their theory, these unions had key characteristics in common with the firms including strong boundaries, pursuit of monopoly, and dependence on institutional legitimacy.  In general, they had their ideological and historical origins in the age of bureaucratic rationalism \citep{hannan_organizational_1989}.   Theories of organizational ecology have been widely applied to organizations in other contexts, most importantly voluntary organizations and social movements \citep{mcpherson_ecology_1983, soule_competition_2008, minkoff_interorganizational_1995, olzak_ecology_2001}.

The best work of this kind meaningfully adapts organizational ecology to the new context.  For example, \citet{soule_competition_2008} link organizational ecology to the resource mobilization theory of social movement organizations. Such works use organizational ecology as a ``theory of the middle range'' that is empirically grounded but has sufficient generality to bridge across multiple domains. However, organizational ecology is not mature paradigm like thermodynamics where models can be treated as ``scientific laws'' and expected to make accurate predictions about new contexts without any conceptual modification \citep{kuhn_structure_1970}.
As discussed above, some basic concepts of theory, like that of the organizational form, are difficult to apply to online communities.
When virtually all organizations in an organizational field are highly distinctive and no established system for categorization can be found, the concept of ``organizational form'' breaks down and so may the usefulness of distinguishing between the ``population'' and ``community'' levels of analysis.   

Despite these ontological concerns, as I argue in Chapter 2, density dependence theory's environmental perspective is still useful because the relationship between user overlap density and growth or survival seems to reflect the hospitality of an environment.
However, one must keep in mind that tests of density dependence theory in online communities have provided evidence in the form of weak correlations derived from observational data.
I suggest that a project to synthesizes foundational concepts from organizational ecology with new empirically supported ideas about the interdependence between online communities will be a more effective strategy.

The most important empirical finding, that mutualism is widespread, is empirically supported by quantitative-qualitative triangulation. Using statistical methods, I have found that mutualism is much more common than competition among subreddits with highly overlapping users. Based on interviews with members of these subreddits, I have found that this widespread mutualism is consistent with their intuitions and I have surfaced a plausible explanation for it in how individuals seek multiple benefits from online communities and that communities with similar topics and overlapping users specialize in providing different types of benefits. 

Online communities provide granular longitudinal data of individual behaviors in overlapping groups that make it possible to effectively model and test such propositions.
Studies in organizational ecology have generally been limited to one organizational form or organizational field at a time.
This has made it difficult to test hypotheses about the scope conditions for ecological dynamics or their consequences.
The time series analysis strategies advanced in chapters 2 and 4 make it possible to study ecological interactions on much larger scale, and to justify statements about what kinds of relationships are typical and to model antecedents and consequences of these relationships.  
It is important to recognize the limits of prior theories and quantitative tools. When results are puzzling or dead-ends are reached, talking to community members is likely to yield insights that open the way toward a solution. The project of this dissertation is to begin reconstructing organizational ecology in the relatively theory-poor but data-rich context of online communities. 

% I reconstruct organizational ecology
%  project.
% infer a large number of competitive and mutualistic relationships groups instead of depending on an elaborate theoretical foundation.  
% Chapter 2 uses this method to deconstruct theories like density dependence that were built upon assumptions of when organizations will be competitors or mutualists by inferring these relationships directly from the data. This begins the
% This widespread mutualism among online communities with overlapping members radically contrasts with the competition found among offline voluntary organizations and follows from important ways that online communities differ from classical organizations.
% The ``openness'' of online communities in conjunction with the use of digital media decrease the rivalrousness of membership, and therefore the potential for competition over members.
% That online communities exist to provide public benefits to their members and audiences and provide different types of benefits at different sizes means that they do not in general seek to increase their sizes. 
% Unlike commercial firms, online communities do not have strong incentives to compete with each other. 
% Many reasons suggest that overlapping online communities will be mutualists and few reasons are apparent for why multiple communities providing equivalent benefits would exist and compete.
% Yet, observing that mutualism is common does not explain the different roles of community founders, managers, and platform design in how systems of overlapping mutualistic online communities are organized.

% Organizational ecology provides evolutionary modes of explanation for organizational change based on adaptation or selection processes \citep{ven_explaining_1995}.
% Early organizational ecology made strong assumptions that organizational cores change relatively little because of ``structural inertia'' introduced by the external homogenizing forces described above and also by internal factors like culture and routines that are difficult to change \citep{hannan_structural_1984}.  
% Most organizations typically have neither sufficient information about their environments nor the ability to coordinate change with sufficient precision in order to rationally adapt, especially when it comes to change in the ``core'' aspects of an organization \citep{hannan_organizational_1989}.
% This model suggested that change in organizational forms was likely to be driven by organizational death and replacement instead of adaptation.

% Paragaph below copied to chapter 4.
% Online communities also appear to have significant inertia that may come from multiple causes discussed above, but it is also conceivable that mutualism can emerge through an adaptive process that their openness makes possible \citep{mcpherson_testing_1996}.
% Suppose an individual chooses to participate in a community when they have the greatest expectation of finding a type of benefit. 
% Through their participation, they can make the community a better place to find this type of benefit by contributing to the supply of resources their own content, attention, and efforts and by rewarding those who provide their benefits with thanks, votes and other signals of approval. 
% When many individuals act in this way, their actions may collectively reinforce the ability of the community to provide the benefits in a process resembling the Schelling model of segregation \citep{schelling_micromotives_1978}.
% When communities overlap, large degrees of specialization may emerge through such a feedback loop \citep{mcpherson_testing_1996}.

% Chapter 4 deepens the exploration of ecological dynamics by relaxing assumptions of the model in Chapter 2 in order to find out how ecological interactions between online communities vary over time and the roles of adaptation and selection in changing ecological dynamics. I test the hypothesis that online communities can rationally adapt to avoid competition or increase mutualism through a time series analysis. The first step is to demonstrate that competitive and mutualistic dynamics in online communities are not static, but dynamic. They vary over time.  Therefore, if online communities act rationally to position themselves relative to each other in ways that optimize their mutualism, we might find temporal correlations between a communities changes topic and membership overlap and its competitive and mutualistic relationships.
% However, I observe that changes in online community topics are not correlated with decreases in competition or increases in mutualism.
% This suggests that the emergence of mutualism is driven not by adaptation, but by selection.
% Chapter 5 discusses future directions to investigate the micro-level dynamics of this process and other open research questions. 
  
% % Cite exit and voice below
% These findings lend additional support to the notion that changing online communities is difficult.  Creating new communities that provide complementary benefits may be an alternative solution when existing communities are lacking.  
% However, the set of new benefits likely needs to be significantly different from the set of benefits provided by incumbent communities.
% Although the results of Chapters 2 and 4 find mutualism is less common than competition, they also show that competition happens.
% Moreover, they look at communities that have survived for long enough that their niches are measurable and therefore competition faced by the smallest communities that never take off is unobserved. 
% If the greater prevalence of mutualism is driven by a selection process, this is likely because new communities that face competition are exceedingly unlikely to survive. 

% As an example, consider attempts to reform Wikipedia to be more inclusive through changing sourcing and notability policy.
% These attempts encounter strong structural inertia resulting from entrenched norms and policies and capacities of opponents to stonewall debate and block changes.
% In this way, activists for a more inclusive Wikipedia have struggled to exercise voice.
% Wikipedia's openness and creative commons licensing make it possible for other encyclopedias to reuse its content. 
% Yet, should activists choose to exit and start an alternative to Wikipedia with different policies, this new project will be unlikely to replace Wikipedia if the differentiating factors are limited to different policies and better coverage in a few areas.
% Still, those seeking a more inclusive knowledge production community or the specific types of knowledge it provides may find these benefits in a new specialized community.
% However, Wikipedia will almost certainly continue to draw a larger audience and pool of contributors.

% Organizational ecology's virtues stem from its defining conceptual move: to explain the success or survival of individual organizations in terms of their relationships with other organizations.
% By adopting an intermediate level of analysis seeking to explain the largest rise of  analytically tractable 
% with ambitions reaching far below explaining macro-historical changes like the rise of capitalism, organizational ecology  dynamics of large-scale social changes like the rise of newspapers or M-form organizational forms, without appealing to overarching macro-historical forces that are difficult to measure and may be necessarily undetermined given available evidence.


% 
% something about institutionalization?

% We will address these shortcomings by first engaging deeply with ecological research in both biology and organization science from which we will borrow concepts and methods. In the context of online communities, we will define an ecological \emph{population} as the set of communities that share a set of \emph{resources}. In the context of online community research, resources include the labor and intellects of participants, content that they appropriate and produce, as well as the technological and social systems that communities develop to structure themselves like norms, rules, and technologies \cite{butler_membership_2001}. In an ecological model, a community must find a \emph{niche}---i.e., a set of resources that it can utilize comparatively better than other communities---in order to survive.  

% Why study online communities from an ecological perspective? 

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% \printbibliography[title = {References}, heading=secbib]
