Festim

www.bournemouth.ac.uk

Festival Impact Monitor

[email protected]

[email protected]


Why this process?

• Benchmark Events and Festivals social

media engagement

• Understand the impact of hallmark events

and festivals using social media

• Understand the nature of audiences at

Festivals and Events


FestIM

FestIM

Evaluation Methodology

Reusable Learning Objects

Trained Individuals


Work to date

• UK Festivals and

Events• Birmingham Mela 2013

• Bournemouth Air show 2013

• Edinburgh Fringe 2013

• Glastonbury 2013, 2014

• Luton Carnival (2012,2013,

2014)

• Notting Hill Carnival

(2012&2013)

• Ponty’s Big Weekend 2013

• International Festivals• Amsterdam Dance Event 2013

• St Patricks Day 2014

• Calabar Festival 2013

• Nice Carnival 2014

• Trinidad Carnival 2013, 2014


Current Event Management

Research

• The events industry is established

• Expositions,

• Sport marketing

• Concert productions,

• However, still new as an academic field of

study and a research topic ( Mair and

Whitford 2013)


Current Event

Management Work

• Impact and evaluation studies including forecasting assessing and evaluating economic and non economic impact such as social development, community structure, social capital, group and place identity

• Motivation and perceptions of visitors and residents

• Environmental studies. Sustainability and greening

• Political studies. Power and politics relationships between governments, event organizers and communities

• Management studies: Festival management, destination management, stakeholders, marketing, CSR and competition


Existing Event

Management Research

Methods• Most research based on single or a few cases, generally within the same

culture and environment as the researcher. (Getz 2010)

• Convenience Samples

• Structural Equation Modelling

• Few whole-population studies have been attempted in the festivals and

events sectors.

• Little research on actual experiences

• Few Cross-cultural comparisons of festivals


Non Economic Impact

Evaluation ApproachesEvaluation

Method

Conventional

Usage

Strengths Possible

Limitations

Survey Stakeholder

analysis,

Participant

Motivation

Low cost,

Multiple options for

distribution

Ignore segments of

population, Relatively

low response rates

Focus

Group

Explore attitudes,

beliefs and

sentiments

Broad exploration

of issues

Difficult to determine

validity of findings,

Relatively expensive

Interviews “” Rich data, Broad

exploration of

issues

Relatively expensive,

Time consuming

Content

Analysis

Value and

sentiment of media

coverage

Wide coverage

and Deep

exploration

Resource intensive,

Relatively slow


Example: Notting Hill

Carnival


Emergence of Online

Computer Media Interaction

• Changes in information technology and devices enable new forms of interaction• Blogs

• Wikis

• Social network sites

• Virtual Communities

• Community of interest • Common interest

• Other social or emotional ties may not be necessary


Social Media data has

been used to predict

• Purchases

• Illness

• Disaster relief efforts

• Stock market

• Why not events?


Online Event research

• Events increasingly host a hybrid

virtual/physical community

• Volume of data

• Census approach vs Sampling

• Authentic (can be sent from festival site)

• Low cost to process

• Supports comparison/benchmarking

• Enables open research: Methods and data

can be made accessible for review


Researching Online

CommunitiesResearcher

Presence

Quantitative Qualitative

Obtrusive/ Reactive Online surveys Online interviews

Online lab experiments Online focus groups

Online field research

Unobtrusive/ Non

Reactive

Quantitative web

content analysis

Qualitative web

content analysis

Social Media network

analysis

Online field

experiments

Online natural

experiments


Underlying topic/

interest communities

Statistical Text

Analysis

Sentiment (Number

of positive and

negative words)Topic Content

Social Media

Narratives + User

Profiles

Social Network

Analysis by user

location and topic


Social network

perspective

• Emphasis on structure of social relations

• Relationships are unit of analysis

• Interdependence of actors


Extracting relationships

from Social Media

• Follows

• Mentions

• Retweets

Person

APerson

BPerson

C

Person A follows

Person B

Person C mentions

Person B in tweet

Person C comments on

Person B’s Facebook

Post

A B C

Social network: Directed, unweighted graph


Real World Networks

• Scale Free

• Distribution of connections may follow a power

law

• Preferential attachment

• Form subgroups with a specific demographic or

topic focus

• These properties can be used to identify

the stakeholder groupings in online event

conversations


• Use statistics to add a numerical

dimension to unstructured text

• Analyze content of conversations in

stakeholder groupings

• Understand the topics of conversations

in online stakeholder groupings

Statistical Text Analysis


Online Event

Classification

• Size (volume of tweets)

• Span (pattern of topic engagement)

• Scope (Geographic range of online

participants )


Luton Carnival (2013)

Amsterdam Dance Event

2013

Glastonbury 2013

Edinburgh Fringe 2013

Notting Hill Carnival

2012/2013

Birmingham Mela 2013

Ponty’s Big Weekend

2013

Bournemouth Air Show

(2013)


Large Live

Audience

>250,000

(Relatively)

Small Live

Audience

< 50,000

Size: Large Virtual Audience > 100,000 interactions

Small Virtual Audience < 10,000 interactions





2012/2013

Birmingham Mela2013

Ponty’s Big Weekend 2013

Amsterdam Dance Event 2013

Bournemouth Air Show (2013)


Glastonbury 2013

Large Live

Audience

>250,000

(Relatively)

Small Live

Audience

< 50,000

Span: Multiple distinct topic communities

Small Span of few large topic communities


Amsterdam Dance Event

2013

Glastonbury 2013



2012/2013


Birmingham Mela 2013

Ponty’s Big Weekend 2013

Bournemouth Air Show (2013)


Large Live

Audience

>250,000

(Relatively)

Small Live

Audience

< 50,000

Scope: Global Presence

Local Presence


Example 1: Love Luton

Festival 2012


Example 2: Notting

Hill Carnival 2013

• Social network analysis was used to identify the key online communities for the Notting Hill carnival

• Overall

• 5081 groups, 31,363 twitter user accounts

• 30 major subgroups within community

• High degree of modularity in network. This means that individuals tend to speak to members within the group far more than they speak to members outside the group


Group

Number

Number

of

Members

Description Topics Discussed

1 1861 International Carnival Nation. Members come from all over

the world and participate in Carnivals in the Caribbean, US,

UK and Europe

Traditional carnival arts of

Steelpan, Calypso, Masquerade

2 1309 London Carnival Nation. Festival performers and fans from

the London Area



3 1056 Young Traditional Carnival Performers and Fans. Based in

London Area, university/college students



4 1034 Soundsystem and Reggae Fans. Range of age groups,

primarily London based with a few members in other parts of

the UK, Jamaica and Europe

Reggae Music, Sound Systems

5 1002 African Diaspora. Carnival participants from Ghana and

NIgeria

Afrobeats Music, Contemporary

African Music and Performers

6 864 Online media masters, coverage of Notting Hill Carnival by

blogs and online media companies

Soundsystems, Reggage,

Traditional Carnival Arts, Festival

Program, Transport

7 671 Media Coverage from Traditional Outlets Soundsystems, Reggage,

Traditional Carnival Arts, Festival

Program, Transport

8 653 Highly engaged online individuals. Young individuals (not

companies)

Visual and viral content of phots

and videos

9 596 Political and intellectual twitter users. Academics and

activists who see the carnival as a political platform

Ethnic issues, Policing, History

10 569 Club Promoters Club nights and parties affiliated

with Notting Hill Carnival


Analysis

• Carnival has an international online presence with interactions from all over the world

• Overall network displays an egalitarian structure:

• No overly dominant account. Largest group is only 5% of overall accounts

• Top 5 Groups are fairly similar in size

• Diverse range of topics discussed

• Distinct subgroupings based on demographics/interests


Challenges/Trends

• 2012 to 2013: Shift to Mobile

• Smartphone saturation is approaching

• Social media platform growth rates slowing

• Online interactions are incorporating visual

elements

• Cost of data collection/analysis is falling

• 2012: Manual

• 2014: Many companies offering on demand

access to streaming data, several offering

historical access


References

Boyd, D., Golder S. & Lotan, G. Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. System

Sciences (HICSS), 2010 43rd Hawaii International Conference on, 2010. IEEE, 1-10.

Borgatti, S. P., & Foster, P. C. (2003). The Network Paradigm in Organizational Research: A Review and

Typology. Journal of Management, 29(6), 991–1013.

Burnett, C. 2001. Social Impact Assessment and Sport Development: Social Spin-Offs of the Australia-South

Africa Junior Sport Programme. International Review for the sociology of Sport, 36, 41-57.

Carrington, P. J., Scott, J. & Wasserman, S. 2005. Models and methods in social network analysis, Cambridge

university press.

Castillio, C., Mendoza, M. & Poblete, B. Information credibility on twitter. Proceedings of the 20th international

conference on World wide web, 2011. ACM, 675-684.

Clauset, A., Newman, M. E. J., & Moore, C. (2004). Finding community structure in very large networks. Physical

Review E, 70(6), 066111.

Crompton, J. L., & McKay, S. L. (1997). Motives of visitors attending festival events. Annals of Tourism

Research, 24(2), 425–439.

Getz, D. (2005). Event Management and Event Tourism. Cognizant Communication Corporation.

Getz, D. 2010, The Nature and Scope of Festival Studies, International Journal of Event Management Research

5(1)2010

Godes, D., & Mayzlin, D. (2004). Using Online Conversations to Study Word-of-Mouth Communication.

Marketing Science, 23(4), 545–560.

Hansen, Derek, Ben Shneiderman, and Marc A. Smith. Analyzing social media networks with NodeXL: Insights

from a connected world. Morgan Kaufmann, 2010.

Kwak, H., Lee, C., Park, H., & Moon, S. (2010, April). What is Twitter, a social network or a news media?. In

Proceedings of the 19th international conference on World wide web (pp. 591-600). ACM.


References

Mair, J. & Whitford, M. (2013) "An exploration of events research: event topics, themes and emerging trends",

International Journal of Event and Festival Management, Vol. 4 I 1, pp.6 – 30

Rollins, R. & Delamre, T. 2007. Measuring the social impact of festivals. Annals of Tourism Research, 34, 805-808.

Sacha, R., Deborah, E. & Katie, S. 2005. Methodological considerations in pretesting social impact questionnaires:

Reporting on the use of focus groups.

Smith, A. 2009. Spreading the positive effects of major events to peripheral areas. Journal of Policy Research in

Tourism, Leisure and Events, 1, 231-246.

Stone, Philip J. "Thematic text analysis: New agendas for analyzing text content." Text analysis for the social sciences:

Methods for drawing statistical inferences from texts and transcripts (1997): 35-54.

Festim

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Transcript of Festim