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Wayne Weiai XuPhD CandidateDepartment of Communication, SUNY-Buffalo

Advisor: Dr. Gregory D. Saxton, Associate ProfessorDepartment of Communication, SUNY-Buffalo

Predicting Social Capital in Nonprofits’ Stakeholder Engagement on Social Media

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THE SOCIAL (MEDIA) CAPITAL MODEL

INVESTMENTSOCIAL CAPITAL

RETURN

Message-based investment

Connection-based investment

Network locations

Embedded resources

Word-of-mouth

Reputation

Context: Community foundations’ public communication on Twitter

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Why another social capital model/term?1.

WHY THE STUDY?

Is social media anything new?2.

Is organizational social capital different from its interpersonal counterpart?3.

Social capital was treated as an outcome or antecedent, rather than a theory (which it really is).

Social media could be a great equalizer in the distribution of social capital.

Mass-interpersonal approach

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A lack of empirical testing of the social capital as a process, rather than an antecedent or an outcome, in particular, in computer-mediated contexts.

1.

THE GAP

A lack of conceptualization and measures of the social capital process unique to the social media context, especially considering that organizations build/maintain online contacts through interpersonal approaches.

2.

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INVESTMENT SOCIAL CAPITAL

Message-based investment

Connection-based

investment

Network locations

Embedded resources

P1

P2P3

P4

STUDY ONE

STUDY MODEL

RETURN

Word-of-mouth

Reputation

P5

P6P7

P8

STUDY TWO

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Twitter mentions/replies, distinguishable by the symbol “@”

MEASURES OF RELATIONSHIP INVESTMENT

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• The cue richness of messages• The number of targeted stakeholders• The frequency of targeting• The variety of targeted stakeholders

• The number of targeted stakeholders• The frequency of targeting• The variety of targeted stakeholders

INVESTMENT

Message-based investment

Connection-based investment

MEASURES OF RELATIONSHIP INVESTMENT

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NETWORK LOCATIONS EMBEDDED RESOURCE

MEASURES OF SOCIAL (MEDIA) CAPITAL

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• In-degree centrality • Betweenness centrality

• The size of acquired stakeholder network• The influence of acquired stakeholders• The strength of ties with acquired

stakeholders• The variety of acquired stakeholders

SOCIAL CAPITAL

Network locations

Embedded resources

MEASURES OF SOCIAL (MEDIA) CAPITAL

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WORD-OF-MOUTH REPUTATION

MEASURES OF RETURNS

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• # of retweets per tweet

• List count• One month increase in list count

RETURN

Word-of-mouth

Reputation

MEASURES OF RETURNS

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U.S.-based community foundationsBased on a complete list of 1,308 community foundations by the Council on Foundations (www.cof.org/community-foundation-locator). 258 were present on Twitter at the time of study

INVESTMENT: Three-month data, 07/30/2014 to 10/30/2014

SOCIAL CAPITAL: Three-month data, 10/31/2014 to 01/31/2015

RETURN: One-month data, 02/01/2015 to 02/28/2015

DATA SOURCE

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• Social (media) capital can be acquired through relationship investment• The best practice is connecting with diverse ties through rich messages

MAJOR FINDINGS

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# of targeted local stakeholders

# of targeted non-local stakeholders

Frequency of stakeholder-targeting

Variety of targeted stakeholders# of tweets

Message complexity

INVESTMENT SOCIAL CAPITAL

the size of acquired stakeholder network

β = .24*

β = .17*

β = .17*

F (8, 193) = 40.99, .61**

RESULTS – HOW INVESTMENT PREDICTS SOCIAL CAPITAL

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# of targeted local stakeholders

# of targeted non-local stakeholders

Frequency of stakeholder-targeting

Variety of targeted stakeholders# of tweets

Message complexity

INVESTMENT SOCIAL CAPITAL

the influence of ties with acquired stakeholders

β = .18*

F (8, 193) = 10.88, .28**

RESULTS – HOW INVESTMENT PREDICTS SOCIAL CAPITAL

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# of targeted local stakeholders

# of targeted non-local stakeholders

Frequency of stakeholder-targeting

Variety of targeted stakeholders# of tweets

Message complexity

INVESTMENT SOCIAL CAPITAL

the strength of ties with acquired stakeholders

β = .20*

β = .29*

F (8, 193) = 10.72, .28**

RESULTS – HOW INVESTMENT PREDICTS SOCIAL CAPITAL

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# of targeted local stakeholders

# of targeted non-local stakeholders

Frequency of stakeholder-targeting

Variety of targeted stakeholders# of tweets

Message complexity

INVESTMENT SOCIAL CAPITAL

the variety of acquired stakeholders

β = .30*

β = .11*

F (8, 193) = 28.17, .52**

RESULTS – HOW INVESTMENT PREDICTS SOCIAL CAPITAL

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# of targeted local stakeholders

# of targeted non-local stakeholders

Frequency of stakeholder-targeting

Variety of targeted stakeholders# of tweets

Message complexity

INVESTMENT SOCIAL CAPITAL

Betweenness centrality

β = .34*

β = .16*

F (8, 193) = 15.05, .36**

β = -.24*

RESULTS – HOW INVESTMENT PREDICTS SOCIAL CAPITAL

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# of targeted local stakeholders

# of targeted non-local stakeholders

Frequency of stakeholder-targeting

Variety of targeted stakeholders# of tweets

Message complexity

INVESTMENT SOCIAL CAPITAL

Indegree centrality

β = .39*

β = .18*

F (8, 193) = 9.70, .26**

β = -.30*

RESULTS – HOW INVESTMENT PREDICTS SOCIAL CAPITAL

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• Acquired social capital helps diffuse organizational messages and build online reputation.

MAJOR FINDINGS

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Betweenness centrality

The size of acquired local stakeholder network

The size of acquired non-local stakeholder networkThe influence of acquired

stakeholdersThe strength of ties with acquired stakeholdersThe variety of acquired

stakeholders

SOCIAL CAPITAL RETURN

Retweet

β = .30*

F (8, 193) = 16.92, .39**

β = .14*

RESULTS – HOW SOCIAL CAPITAL PREDICTS RETURNS

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Betweenness centrality

The size of acquired local stakeholder network

The size of acquired non-local stakeholder networkThe influence of acquired

stakeholdersThe strength of ties with acquired stakeholdersThe variety of acquired

stakeholders

SOCIAL CAPITAL RETURN

list count

β = .17*

F (8, 193) = 116.55, .82**

β = .27*

β = -.08*

RESULTS – HOW SOCIAL CAPITAL PREDICTS RETURNS

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Betweenness centrality

The size of acquired local stakeholder network

The size of acquired non-local stakeholder networkThe influence of acquired

stakeholdersThe strength of ties with acquired stakeholdersThe variety of acquired

stakeholders

SOCIAL CAPITAL RETURN

One-month increase in list count

β = .19*

F (8, 193) = 20.95, .44**

β = .22*

RESULTS – HOW SOCIAL CAPITAL PREDICTS RETURNS

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Centrality

The size of acquired local stakeholder network

The size of acquired non-local stakeholder network

The influence of acquired stakeholders

The strength of ties with acquired stakeholdersThe variety of acquired

stakeholders

SOCIAL CAPITAL# of targeted local stakeholders

# of targeted non-local stakeholders

Frequency of stakeholder-targeting

Variety of targeted stakeholders# of tweets

Message complexity

INVESTMENT RETURN

# of retweet per tweet

List count

Increase in list count

RESULTS – MEDIATED RELATIONSHIPS

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An empirical testing of social capital as a (causal) process

CONTRIBUTIONS

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The development of measurement scheme for social media capital2.

Further empirical or philosophical debates on whether social capital is inherited or acquired3.

Practical implications in strategic Twitter communication4.