Analyzing Community Websites:
A Main Street Perspective

Sheryl R. Schoenacher
sheryl.schoenacher@farmingdale.edu
Computer Systems Department
Farmingdale State College
Farmingdale, NY  11735, USA

Abstract

Community websites are a commonplace occurrence.  Studies have examined those of larger cities, but lacking in the literature was the examination of those sites that represent small local communities—those with a Main Street business center.  This study analyzed ten community websites all of which have a Main Street business center with the purpose of creating the ontology of social, political, economic, and cultural characteristics found on these websites.  Each main category supported subcategories. The results indicated the commonalities among sites as well as those aspects that are not as prevalent. Most town sites were created by local government. Only one town had a site created by town residents. Main Street merchants were not well represented by these community sites.

Keywords: Main Street, community websites, small towns, information access


1. INTRODUCTION

Community websites have been both hailed as the panacea for globalization and the antecedent of community disintegration.  The reality is that both views meet somewhere in the middle.  The development of a website is neither the solution to small-town community ills nor is it the signal of the impending demise of community. What is agreed upon is that information technology and the Internet are great media for the sharing of knowledge. As such, it is valuable to explore how small communities seek to share information via the web and to what extent this information is socially, economically, politically, and culturally driven.

This exploratory study examines the representative websites for ten towns in Nassau County, New York, that have a Main Street business community in order to create the ontology of their characteristics. Ontology is an important emerging discipline that has the huge potential to improve information organization, management and understanding (Ding and Foo 2002). The role of ontology creation is to improve how information is represented in such resources as Internet websites. 

This study focuses on Main Street communities as they represent a unique segment of residential life. Main Street is a place to shop where merchants recognize their customers by name. Shopkeepers know that customer service and quality merchandise is what distinguishes them from big box stores (Schoenacher 2008). Wal-Mart may be pulling the dollars from consumers, but the heart and sole of the consumer remains with the small retailer (Buchanan 2002).  The street is much more than just a place to shop. 

People need a “third place”, outside of work and home, where they can connect with others. If home is the first place, and work the second, then the information meeting town, 
in town, at a village green, or on a main street is the third (Osborn 1951).

Main Street business centers struggle to compete with their historical nemesis, the suburban mall, as well as national chain stores and the big box retailers. 

The disturbing reality is that more and more American towns and cities—especially those that would like to preserve their local cultures and to grow their own local retailers and innkeepers—are facing a tough dilemma (Peirce 2004).

For the purposes of this study, the defining characteristics of a Main Street were those set forth by Francaviglia whose life work was focused on the American landscape and, specifically, its romantic attachment to Main Street, USA. A Main Street is synonymous with the downtown commercial area or district of the small town. A small town, as defined by Francaviglia, had a population greater than 750 and fewer than 30,000 people (Francaviglia 1996). Communities with less than 750 people were more likely to be referred to as hamlets, and communities with more than 30,000 people as small cities (Francaviglia 1996).

2. REVIEW OF RELATED LITERATURE

Although community websites have been analyzed from a variety of perspectives, the literature is lacking when it comes to the examination of websites as they represent small communities—those with a Main Street business center. Some perspectives that have been studied include the examination of larger city websites, smart communities, community informatics, and community networks. Research relating to these viewpoints was discussed in this section.

Twenty websites of large cities were analyzed to ascertain if the website for these cities accurately depicted their physical city counterpart. Characteristics such as city size, income level and global presence were compared to the city’s website to see if any of these characteristics affected the city’s website design or its contents (Urban 2002). The study indicated that there was no relationship between the size of the actual city, the income level of residents, or global presence and the size, design, and content of the its representative website. The researcher set up categories of website features including transportation, tourist services, news and events, and links to other cities. The makeup of the real city and the contents of its virtual city had little association.

Smart communities are defined by their ability to represent the social, economic, and cultural aspects of a city or town. These virtual communities have the purpose of improving the quality of life, fostering economic development, and increasing the success of city administration. The authors of this study found that smart communities can also foster safer communities (Kervern, Eger et al. 1999). In addition, these virtual communities when combined with collaboration from government, business, academia, etc., created the potential for global competitiveness.

Community informatics (CI) is a concept that utilizes the Internet as an information and communication technology (ICT’s) to provide community building and development. In this study, the authors assessed community informatic projects based on their social, political, and economic effects (O'Neil 2002). Theories used to measure the impact of CI projects fell into five areas: strong democracy, social capital, individual empowerment, sense of community, and economic development opportunities. The result of the paper was to establish certain measurements as evaluation tools. In addition, suggestions for the evaluation of future projects were provided.

Community networks support local neighborhoods in the sharing of information, creating discussion, and fostering engagement between residents. What these authors found is that to a great extent the development of these networks do not involve the input of neighborhood residents, but are often created via a standard template provided by a website development firm (Carroll and Rosson 2003). It was argued that local people will become more involved with the use of the network when they are included in the planning and design phases of the network construction.

3. METHODOLOGY

This work continued the study of 10 communities with Main Street business centers that had been previously studied in May 2008 (Schoenacher 2008). Representative websites from these same 10 communities with Main Street business centers in Nassau County, New York, were analyzed using conceptual analysis. The sample of 10 towns was of varied median income taken from 2000 Census data and was chosen using a purposive non-probability sampling strategy from a list of 30 towns. This list of 30 towns with Main Street business centers was compiled with the assistance of the Economic Development Agency and the Council of Chambers of Commerce of Nassau County and was established as a component of previous doctoral research (Schoenacher 2008). The names of these towns were kept anonymous as was required in the previous study. The towns were referred to as Town 1 through Town 10.

Using Google as a search engine and town name as the search query, representative websites for each town were collected.  A representative website for the purposes of this study was the most informative site existing for that town at the time of access. Of the 10 town websites studied, 7 towns had an official website. An official website in this case indicates a general, all-purpose site established by the local town government or residents. Three of the towns did not have an official website, but had a site either established by a Chamber of Commerce or civic association. One town, Town 2, had two equally informative sites: one established by town residents (2A) and another by the local town government (2B). 

Each website was examined to ascertain the type of information available from the site. From this analysis, clues or types of information were classified into four main character categories: social, political, economic, and cultural. Using an Excel spreadsheet, all occurrences of character clues were recorded and counted.

4. FINDINGS

Based on the types of information or clues found, subcategories were established within each of the social, political, economic and cultural main categories. 

There were 3 clues that represented the social character category resulting in the events and meetings; discussions and forums; and communities of interest social subcategories. 

There were 9 clues found in the political character category resulting in the local community organizations; nonlocal organizations; government policies; government services; emails to officials; planning and development; access to forms; government activities; and political action subcategories. 

There were 5 clues found in the economic character category resulting in the local business representation; weather; nonlocal business; transportation; and new business attraction subcategories. 

There were 7 clues found in the cultural character category resulting in the publications; education; town image; historical data and artifacts; libraries; religious institutions; and parks and recreation subcategories.

Main Categories

Of the four main categories, there were 51 (11%) clues occurring in the social character category. This finding would seem to provide a relatively weak opportunity for social interaction via these sites especially considering that 18 (35%) of these social clues occurred on the site of Town 2—almost exclusively from the site established by town residents (2A).

There were 257 (53%) clues found at these sites that represented political character. This is not remarkable as 7 of the 10 town sites were established by the local government. This represents more than half of all clues.

There were 39 (8%) economic character clues found. This would not indicate a strong support for local businesses.

There were 138 (28%) cultural character clues found. Although this would seem to demonstrate a significant level of importance for cultural activities and information, the overwhelming number of these clues occurred on the websites of Town 2, specifically from the site developed by residents (2A) with 83 clues or 60% of the total cultural clues found on all sites.

Figure 1

Subcategories

Examining each main category individually, there were subcategories that were well presented in each area as well as subcategories with a fairly low presence.

In the social character category, 67% of all clues announced events and meetings, 31% offered discussions and exchanges, and 2% represented a community of interest. The discussions and exchanges subcategory represented general interaction among residents on various topics. The community of interest subcategory addressed a particular topic. It should be noted that the greatest number of these social clues were found on the Town 2 website established by residents (2A).  Although only the website of Town 2 created by residents (2A) contained a community of interest, it was a significant finding deserving a unique subcategory. The Town 6 website contained 13 clues in the discussions and exchanges category as this site was a civic association site that solely fostered interactive discussion on various local topics of interest. See Figure 2.

Figure 2

Under the political character category, 25% and 21% of clues represented local and nonlocal organizations respectively. An example of a local organization was a local historical society. An example of a nonlocal organization was the US Post Office. It was interesting that the Town 2 website established by residents (2A) had 76 or over 90% of all clues referencing organizations both local and nonlocal in nature. Government policies represented 14%; government services, 12%; email to officials, 10%; planning and development, 7%; access to forms, 5%; government activities, 5%; and political action, 1%. The political action subcategory allowed residents the opportunity to speak out on local issues of concern. Only Town 2 and Town 6 offered this on their websites. See Figure 3.

Figure 3

In the economic character category, there were 24 (62%) economic clues to local business representation. The Town 2 site contained 10 of the 24 business representation clues. Towns 4, 5, 6, 8, and 10 had no reference to local businesses. Considering the harshness of times for Main Street merchants, this was surprising and showed a lack of support for local businesses. Towns 3 and 9 where representative sites were established by the Chamber of Commerce included a directory of members, but no specific information about each member. There were 7 clues to the weather forecast, 4 to nonlocal businesses, 3 to transportation (bus, train, or taxi), and 1 clue to the new business attraction. In a time of empty storefronts, community websites were not efficiently used of to bring new merchants into the town.

Figure 4

The cultural character category was represented by the second highest number of overall clues. The publications subcategory contained 56 clues or 41% of this type of clue. Publications included brochures, pamphlets, newspapers, and books. The education subcategory contained 35 clued or 25% of all cultural clues and included any link to schools and scholastic resources. The website for Town 2 established by its residents contained the greatest information reference to these two subcategories with 83 clued or 93% of all of these types of clues. Towns 1, 3, 4, 8, and 10 had no reference to their schools.

Figure 5

5. DISCUSSION

In examining the findings, characteristic similarities existed among community websites with Main Street business centers.  Each website had some social, political, and cultural characteristics. Towns 4, 6, and 8 had no economic characteristics. This was quite surprising and may indicate a hostile relationship between local government and local businesses. Although these results cannot be used as a generalization of all towns with Main Street business centers, this trend demonstrates a true lack of support for the local merchants in these towns.

Towns with Main Street business centers have as their foundation local businesses. A vital Main Street business center creates a prosperous community and a resulting satisfaction in the quality of life (Stans 1946). Local merchants have a stake in the success of the community and tend to invest in both dollars and in spirit (Putnam 2000).

Some towns have invested more time and money in creating a website with greater information intensity—a large number of information resources. Town 2 was the only town that had a website that had been created by town residents. It is not possible from this study to state the usage of each site, but this resident-produced site also had exceptional information density—an in-depth treatment of each topic. There was information about all areas of personal and community life making it possible for residents to consider their community website a portal. Information lacking in this site was completed by its second site that had been created by its local government.

The primary content of these sites studied was political in nature. This is not remarkable considering that most of the community websites were established by the local government. However, websites will be used more when community residents are involved in its creation (Carroll and Rosson 2003). Informational resources placed on a website should be based on the mutual interests of both government and citizens.

By establishing the ontology of community website characteristics (See Appendix A), future projects may draw upon the results. A checklist of sorts can be developed as part of the project analysis stage. Using the Town Comparison (See Appendix B), towns can see how their sites rate against others in terms of what type of information is available on their community websites compared to other towns and, therefore, obtain ideas about improving their individual sites.

6. IMPLICATIONS FOR FUTURE RESEARCH

Research inherently opens up more questions as a result of its findings. It was not the focus of this study to compare towns or to compare the physical town with its virtual website. However, this would be a valuable next step. How does the physical town with a Main Street business center compare to its representative virtual site? Is there a relationship between town median income or size and their representative websites?

The findings of this study indicate that there was a limited opportunity for social interaction via the community website. How does the level of social interaction or social capital within the physical town compare with that in the virtual realm?

The answer to these questions and those answered by this study can help the small town and its local merchants prosper. 





7. REFERENCES

Buchanan, L. (2002). America's Favorite Hometown Businesses. INC. 24: 63-76.
Carroll, J. M. and M. B. Rosson (2003). "A Trajectory for Community Networks." The Information Society 19(5): 381-393.
Ding, Y. and S. Foo (2002). "Ontology Research and Development. Part I--A Review of Ontology Generation." Journal of Information Science 28(2): 123-136.
Francaviglia, R. (1996). Main Street Revisited: Time, Space, and Image Building in Small-Town America. Iowa City, University of Iowa Press.
Kervern, G.-Y., J. M. Eger, et al. (1999). "Smart and Safe Communities". 9th Annual Conference of the Internet Society, San Jose, CA, Internet Society, [Access Year]. Available from http://www.isoc.org/isoc/conferences/inet/99/proceedings/.
O'Neil, D. (2002). "Assessing Community Informatics: A Review of Methodological Approaches for Evaluating Community Networks and Community Technology Centers." Internet Research 12(1): 76-102.
Osborn, R. C. (1951). "The Plea for Small Business." The Accounting Review 26(4): 540-554.
Peirce, N. (2004). Will the Chains Swallow Main Street? Nation's Cities Weekly: 2.
Putnam, R. (2000). Bowling Alone. New York, Simon & Schuster.
Schoenacher, S. (2008). "The Information-Gathering Behavior of Main Street Merchants". Northeast Business & Economics Association 35th Annual Conference, Melville, NY, Northeast Business & Economics Association, [Access Year]. Available from 
Schoenacher, S. (2008). The Information-Gathering Behavior of Main Street Merchants and the Effect of Social Capital on Information Access. The Palmer School of Library and Information Science. Brookville, Long Island University: 356.
Stans, M. H. (1946). "What Small Business Needs." The Accounting Review 21(4): 361-371.
Urban, F. (2002). "Small Town, Big Website? Cities and their Representation on the Internet." Cities 19(1): 49-59.


Appendix A. Community Website Ontology:
 A Main Street Perspective





Appendix B. Town Comparison
Analyzing Community Websites: Comparing Towns 1-10
Social, Political, Economic & Cultural Characteristics

1
2A
2B
3
4
5
6
7
8
9
10
Total in
Clue
Category
% of
Total
Clues
Social Character Clues













Events & Meetings
3
13
1
2
6
2
0
3
1
2
1
34

Discussions & Exchanges
0
3
0
0
0
0
13
0
0
0
0
16

Communities of Interest
0
1
0
0
0
0
0
0
0
0
0
1

Total Social Character Clues
3
17
1
2
6
2
13
3
1
2
1
51
11%
Political Character Clues













Local Community Organizations
3
36
7
1
2
0
13
1
0
2
0
65

Nonlocal Organizations
0
40
4
1
0
0
0
0
0
2
7
54

Government Policies
5
0
10
0
5
4
0
2
4
0
6
36

Government Services
5
6
4
0
0
2
0
7
3
2
2
31

Email to Officials
2
0
5
2
1
1
0
7
1
2
4
25

Planning & Development
0
1
3
0
2
2
4
0
5
0
0
17

Access to Forms
6
0
0
0
1
1
0
2
2
0
2
14

Government Activities
1
0
2
0
2
4
2
0
1
0
0
12

Political Action
0
1
1
0
0
0
1
0
0
0
0
3

Total Political Character Clues
22
84
36
4
13
14
20
19
16
8
21
257
53%
Economic Character Clues













Local Business Representation
4
10
6
2
0
0
0
1
0
1
0
24

Weather
0
1
2
0
0
1
0
0
0
1
2
7

Nonlocal Businesses
0
2
0
0
0
0
0
0
0
2
0
4

Transportation
1
2
0
0
0
0
0
0
0
0
0
3

Attraction of New Businesses
0
0
0
0
0
0
0
0
0
1
0
1

Total Economic Character Clues
5
15
8
2
0
1
0
1
0
5
2
39
8%
Cultural Character Clues













Publications
0
52
1
0
0
1
0
0
0
2
0
56

Education
0
28
2
0
0
2
1
1
0
1
0
35

Town Image
7
1
4
1
3
2
0
1
0
1
0
20

Historical Data & Artifacts
2
0
4
0
1
3
0
2
1
1
0
14

Libraries
0
1
1
0
0
1
1
1
1
1
1
8

Religious Institutions
0
1
1
0
0
0
0
0
1
1
0
4

Parks and Recreation
1
0
0
0
0
0
0
0
0
0
0
1

Total Cultural Character Clues
10
83
13
1
4
9
2
5
3
7
1
138
28%
Total Clues (All Categories)
40
199
58
9
23
26
35
28
20
22
25
485