Perception of e-mail as a significant factor in information overload

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Thomas Virgona

DIS899 (b)

Summer II 2002

 

Professor Amy Spaulding

Palmer School of Library and Information Science

 

 

 

 


 

 

 

 

Table of Contents

 

Abstract..................................................................................................................................................................... 3

Introduction............................................................................................................................................................ 4

Information Overload and Information Studies.......................................................................... 7

Defining Information Overload................................................................................................................. 9

Information Overload – Self Help Solution(s)............................................................................. 12

Research.................................................................................................................................................................... 14

Discussion and Findings.................................................................................................................................. 16

Conclusions........................................................................................................................................................... 17

Appendix Section.................................................................................................................................................. 20

Appendix A – Electronic Mail Survey................................................................................................... 20

Appendix B – Frequency Distribution.................................................................................................... 23

Resources................................................................................................................................................................. 26

 

 


 

Abstract

 

The phenomena known as electronic mail is growing throughout all segments of society.  The low expense and ease of use is enabling students, working professionals and people separated geographically from one another to easily communicate with one another.  While growing and diffusing throughout the globe, a disturbing trend is emerging.  Despite the power of the tool, users of this innovation sometimes feel overwhelmed by the volume of messages that can be generated with electronic mail.  As a result, many users are now reporting that electronic mail is contributing to information overload.

Ironically, in an attempt to stem the information overload problem, the developers of the tool provide features to assist in managing the effects of vast messages that are generated.  In another conflicting piece of data is that more and more people feel that electronic mail contributes to information overload but users of the tool still consider it to be a valuable mode of communications.  One psychological result is working professionals will mentally calculate the task of addressing electronic mail while out of the office.  The volume contributes to the concept of exformation.  Exformation refers to the mental thought process conducted to create or respond to a message is reduced greatly by the amount of pending messages.  The reduced time spent on each message increases exformation, or the information excluded from the communication.


Introduction

 

 

            Pagers, Cell phones, Blackberry, electronic mail (email), voice mail, videoconferences, etc.  All are relatively new innovations over the last twenty years design to improve and facilitate communications.  Have these new communications devices advanced personal and group communications or have they had a negative impact.   Stephen Roach of Morgan Stanley Dean Witter believes we have entered into a trap, working 24/7 (Roach 2002).   "Courtesy of laptops, cellphones, home fax machines, and other appliances, knowledge workers are now online in cars, planes, trains, and homes, virtually tethered to their offices.    Technology will burnout human beings.  The 24/7 culture of nearly round-the-clock work is endemic to the wired economy. Acceleration of productivity growth through hard work alone isn't sustainable: People simply can't work harder and harder indefinitely. That's a lesson that should not be lost on America and its brave new economy."

The impetus for this research stems from the anecdotal stories of electronic mail users.  Many people of all works of life are now using eMail for interpersonal and professional communications.  The power and convenience of this mode of communicating without boundaries is vast.  The low expense, or in some cases no cost at all, has removed the economic barriers of diffusion and adoption.  Ease of use and low training time allows users email to be up and running in a matter of minutes.  The actual use of the tool has become the larger issue, especially when used to communicate to people less than 50 feet away (Losee 1989).  The power to send to multiple parties, discussion groups, add attachments, read and send at any time of the day or night are desirables features.  The year 2002 shows a growing trend to wireless electronic mail, which started approximately ten years ago.  Blackberry and Palm devices are becoming more prevalent and less expensive.  These wireless communication devices come with interesting notification features, such as a vibrating alert.  Ironically, the vibrating alert feature is used so people in close proximity are not bothered by the alert.  However, the attention of receiver of the message is distracted by the message and subsequently changes their focus to the medium.  Although not in disturbed originally by the alert, the awareness of the receiver message is ultimately distracted from others around them, probably causing a higher level of annoyance.

At the root of this discussion is the term communication.  The Shannon-Weaver Communication model contains six components of communication (Underwood 2002):

·        A source

·        An encoder

·        A message

·        A channel

·        A decoder

·        A receiver

Analysis of this model includes the criticism that the message can be separated from the process.  This is in direct contrast to McLuhan's feeling that the medium is the message.  The model does discuss semantic noise, which is at the core of the information overload concept.  Although difficult to define, semantic noise is at the very essence of the study of human communication, concerning itself with people's knowledge level, communication skills, experience, prejudices, etc. (Underwood 2002).  Human beings process information based on life experiences, education, medium, etc.  Something that is written makes it feel more permanent resulting in a little more anxiety than in just talking.  Phone conversations are in real time, and one has other parts of the message than just the words  - tone, pauses, etc.  In general, one can be spontaneous on the phone, but find email uncomfortable (Spaulding 2002).

 

T.D. Wilson, Professor Emeritus in Information Management, University of Sheffield discusses how information overload is not a new phenomenon.  The potential for overload has existed ever since information became an important input to any human activity (Wilson 2001).   Wilson believes once the scientific disciplines began to clearly emerge in the 17th to 19th centuries, it gradually became impossible for anyone to keep abreast of all of the works in a discipline. In some fields, the degree of specialization is so high, even within the same discipline, people are unable to keep abreast of all sub-areas and, in fact, may be completely unable to understand some of them.  Common sense indicates the proportions are vastly different.  As Wurman writes, a typical weekday edition of The New York Times contains more information than the average person was likely to come across in a lifetime in seventeenth-century England. (Nelson 2001)

More recently, the commercial information vendors have taken an interest in the subject, since it is in their interests to ensure that the information load on managers and executives is not so great as to preclude use of their services.

 

            With this growing information overload trend, what is the down side?  Do users of this method of communication feel this is a benefit, or an intrusion on their life, allowing for limited separation between work and home?  Should the discipline of Information Studies be concerned with this phenomenon?  Is there a historical basis for the research?  To resolve these questions, a historical retrospective is required.

 

Information Overload and Information Studies

 

Information science, in its broadest sense, stands for the systematic study of information and may include combinations of other academic disciplines (Machlup and Mansfield).   Scholarly research relating specifically to information overload and its subsequent relationship to electronic mail can be traced back to the writings of Marshall McLuhan and Norbert Weiner.  Their writings starting in the mid-1900’s to the late 1900’s show the growing convergence of technology and communication, and the resulting benefits and problems. While focusing on the impact to the field of Human Computer Interface, cultural and societies changes are discussed.

 

McLuhan’s view is dramatic in the sense that he believes electronic modes of communications will reshape communication (Kostelanetz 1967).  The overriding theme in McLuhan’s world is that the “medium is the message".  McLuhan’s belief that contemporary man experiences numerous forces of communication simultaneously, often through more than one of his senses.  The result will be less content focus and more skimming, similar in the way newspapers are read.  “In his over-all view of human history, McLuhan believes in four great stages: (1) Totally oral, preliterate tribalism. (2) The codification by script that arose after Home in ancient Greece and lasted 2,000 years. (3) The age of print, roughly from 1500 to 1900. (4) The age of electronic media, from before 1900 to the present. Underpinning this classification is his thesis that "societies have been shaped more by the nature of the media by which men communicate than by the content of the communication." (Kostelanetz 1967).  One can sense McLuhan’s fear of whether this new technology is a benefit to society in general.

Fifty years ago, Norbert Weiner proposed that a society could be understood through a study of the messages and the communication channels that belong to culture (Boyer 2002).  “He saw a world that focused on information, not energy; and on digital or numeric processes, not machine or analog. His theories not only laid the foundation for this new field of study, they also largely predicted the future development of computers.” (Jones 2002)

While not a radical new phenomenon, scholars have predicted with some precision and accuracy the merger of technology and communication and the resulting societal impact.  Concerns have now grown past the workplace and into society in general, being held hostage by an inundation of information, which threatens to exceed our ability to manage it (Nelson 2001). Information overload costs businesses and individuals valuable time, effort and additional resources... and the cost is rising.  

In a related information science field, information literacy is concerned with information access.  Horton, in the 1983 article “Information literacy vs. computer literacy” in the Bulletin of the American Society for Information Science, joins the literacy and overload debates (Nelson 2001).  Information literacy can be defined by the “people'' aspect of information access, raising the levels of awareness of the knowledge explosion and involving understanding as to how technology can help identify, access, and obtain data and documents needed for problem solving and decision making.  The inability to merge knowledge and information studies limits both disciplines and is unreasonable (Machlup and Mansfied).

To determine if information overload is truly a growing concern, one must define the basic term: Information Overload.

Defining Information Overload

 

            No one definition of Information Overload is sufficient to cover the multitudes of interpretations and individual preferences.  However, a working research definition is required.  Several individuals have attempted to define the term and the result is a common set of terminology. 

From academia, at the University of St. Gallen, Martin Eppler poses the definition: “Information Overload is a state where the individual is no longer able to effectively process the amount of information he or she is exposed to.  The result is a lower decision quality in a given time set.”   Other academia may have a different perspective on information overload.  According to John Naisbitt, some scientists claim it takes less time to do an experiment than to find out whether or not it has been done before. (Nelson 2001)

A slightly more business and economic definition comes from various sources.  For example, Losee defines information overload as the economic loss associated with the examination of a number of non- or less-relevant messages, as in related information retrieval models (Losee 1989). 

Another perspective relates to the cognitive definition of information overload. Information overload is the inability to extract needed knowledge from an immense quantity of information for one of many reasons. Wurman explains that information overload can occur when a person (Nelson 2001):        

·        Does not understand available information.

·        Feels overwhelmed by the amount of information to be understood.

·        Does not know if certain information exists.

·        Does not know where to find information.

·        Knows where to find information, but does not have the key to access it.

            On the internet, arguably the largest source of information overload, one writer (Anonymous 2002) delineates how specific types of electronic email contribute to information overload.

Time wasting - it’s easy to waste time reading and sending e-mail (just as it is easy to waste time surfing the web). You feel that you have been busy and you have been doing something useful when in fact you haven’t accomplished anything. This is not to say that e-mail isn’t useful. It can be real work that you are doing, e.g. organizing a conference, and discussing a research proposal.

Junk - is also known as unsolicited commercial e-mail and spam. It can be adverts for making money fast, slimming treatments, free holidays. They aren’t paying to send it but you might be paying to receive it.

Attachments - some people won’t open attachments incase they contain a virus. It is bad enough passing on a virus to an individual. If you send an attachment with a virus to a list, you upset many more people. They should be used with care: check that the other party is happy to receive them.

Flames - debate on a list can degenerate into name calling with angry messages fly backwards and forwards

Chat - lists can be used more for social than scholarly purposes.

Confusion - it can be more difficult to convey nuances of meaning when you don’t have the aid of gestures and repetition. Discussions can move on rapidly on a list.

Repetition - you find on lists that the same questions are asked over and over again.

 

For the purposes of this research, the Eppler definition will be used for its inclusion of the cognitive impact of the problem.

 

Information Overload – Self Help Solution(s)

 

That is not to say the information overload problem has gone undetected.  The same tools that present the problem actually offer some simple solutions to manage the chaos.  These tools utilize artificial intelligence to learn behavior and preferences of a particular user. Farithorne argues that computers are not capable of this task and require tedious instructions.  To combat these obstacles, many companies have attempted to address the problem.

 

ZD Net, a technology publisher, has provided some mailbox management suggestions to reduce stress and optimize the use of electronic mail.  (Berst 2000):

Automate tasks: If you always include contact information when you sign your emails, create a signature. If you always forward mail from certain senders to someone else, automate the procedure. If you haven't created work group aliases, set them up.

Preview messages: How many messages do you really need to open? Sometimes I can glance at the subject line to know I can hit delete. Other times I need a little more info. The preview pane integrated in Outlook 2000 allows me to quickly scan an email without opening it, and scroll by pressing my spacebar. Click for more.

Discipline yourself: Efficiency experts recommend dealing with a piece of paper only once. That's good advice for managing email, too. Once a message arrives, read it and act on it. Delete it. Respond to it. File it. Click for more.

Don't duplicate: Announce your preferred means of communication. How many times has someone emailed and faxed you identical information -- and then phoned to see if you received it? That kind of duplication is a time sink -- for everyone involved.

Stay safe: Email viruses can create one of the biggest time sinks you'll come across. And we've had way too many of them in recent months. Be vigilant, even skeptical when you receive mail from someone you don't know. Make sure your anti-virus software is up to date.

 

            Sophisticated electronic mail managers have entered the marketplace with limited success.   The design of these tools is dependent on artificial intelligence, which learns by experience. These tools performs electronic email tasks, such as prioritize, delete, forward, sort and archive mail messages on behalf of the user.  Problems with the early adoption of this technology include (Maes 2002)

·        The first problem is that of competence: how does an agent acquire the knowledge it needs to decide when to help the user, what to help the user with, and how to help the user?

·        The second problem is that of trust: how can we guarantee that the user feels comfortable delegating tasks to an agent?

 

As computers are used for more tasks and become integrated with more services, users will need help dealing with the information and work overload. Interface agents change the style of human-computer interaction. The user delegates a range of tasks to personalized agents that can act on the user's behalf. The artificial intelligence, the agent gradually learns how to better assist the user.

Research

 

                In an effort to determine if electronic mail is seen as a contributing factor of information overload, a survey was conducted.  The survey was distributed to commuters on the Long Island Rail Road in New York.  The target audience was working professionals commuting between Long Island and New York City.  This audience is working professionals largely dependent on information for their livelihood. 

            The surveys were distributed on the westbound morning trains and eastbound evening trains.  One of the assumptions was the pool of possible respondents was broad based, covering a large array of educational, ethnic and professional areas.  The results of the surveys indicates the sample population this was more narrowly focused than anticipated.    

Sixty Six percent of respondents were Caucasian, 81% held a Bachelors/Master’s degree, 72% worked in the corporate world and 60% have one-to-three children.  Given the fact that the Long Island Rail Road is the largest commuter railroad in the country, a larger crosscut of society was expected.

            The questions were formulated to determine if information overload was a growing problem.  Despite the diversity of definitions for information overload, not one respondent asked for a clarification of the term.  All people surveyed not only willingly took the survey, but enjoyed talking about the topic. Upon reflection on the construction of the survey questions, a question asking how many emails per day each respondent received would have been beneficial to the research.

In addition to the information overload question, several related questions were posed.   Do people delete electronic mail without reading the message?  This opens up the topic of entropy. Entropy is a measure of an amount of information we have no interest in knowing (Norretranders 1998). 

Also of interest was the cognitive impact of electronic mail.  Has this innovation become so pervasive that users of this tool find it burdensome? Exformation is about the mental work we do in order to make what we say understood by the receiver of the message.  Exformation is the discarded information, everything we do not actually say but have in our heads when or before we communicate anything at all (Norretranders 1998). With the increasing volume of messaging, can effective communication continue or is exformation growing and information decreasing?  Norretranders discusses exformation in terms of editing one’s idea in light of context known to be shared between  writer and reader.  His example of Hugo’s question mark is great,  because its brevity makes the point in a startling way.   Clearly both publisher and author knew he referred to Les Miserables (Spaulding 2002).”

 

The results of the surveys were entered into a Winks database for analysis.  The Winks software product provides statistical reporting functions.  The data is stored in a database and can easily be exported to other tools for further analysis.

 

Discussion and Findings

 

            After reviewing the findings of the survey, several conflicting patterns emerge.  The results of the surveys indicate electronic mail is contributing to information overload.  Sixty-four percent of respondents indicate that email contributes to information overload.  However, 100% of those surveyed believe email is a valuable mode of communications.  The paradox is that people feel somewhat overwhelmed by electronic mail, but still feel it is valuable too to communicate.

One of the more interesting findings came from the question asking how many electronic mails do you delete on a daily basis without reading.  There was a significant range in responses, from 0 to 500.  A follow up conversation with the respondent who deletes 500 emails per day stated the source of many of the 500 deleted messages was a network server monitoring tool designed to provide information on possible hardware problems.  The tools purpose was to inform critical resources of potential system problems.  However, due to the sensitivity of the monitoring tool, the tool generates such a large volume of messages, it defeats its primary function.   The message gets lost in the medium.  A more representative metric to the question is 24% of the people surveyed delete 10 emails a day without reading the message.

            “One of the keywords in cognitive science is representation (Machlup and Mansfield).”   An increasing number of messages are now being represented in electronic mail format.  As a result, electronic mail does have a growing relationship in the cognitive disciplines.  Forty-five percent of those surveyed like the idea of no electronic mail day.  Fifty-seven percent of the respondents access their professional electronic mails from home.  This would indicate a desire to escape from electronic mail communications.   Despite the physical separation from work and home, the lines are becoming blurred due to technological advances, which easily allows access to corporate communication systems.

 

 

Conclusions

 

Using Roger’s theory of diffusion, one could argue all of the respondents of this survey are early adopters of electronic mail.  Despite deep market penetration in cosmopolitan areas, the vast majority of the populace does not use electronic mail.  For this reason, a longitudinal study is appropriate in this situation.  Over time and as electronic mail becomes more pervasive in society it would be interesting to see if people’s perception that electronic mail contributes to information overload. 

Cognitive research could center on apprehension created by electronic mail.  The research conducted indicates almost half of the respondents mentally calculate the number of electronic mail messages they will receive when they are out of the workplace.  In areas where electronic mail is becoming the primary communication mode, replacing phone and meetings, the advantages of the medium may become outweighed by the disadvantages.  

Massive volumes of these messages may also contribute to the phenomena known as exformation.  Pressure to address the large number of messages will cause a decrease in the time a response can be formulated, not allowing for full attention to the message and meaning.  As a result, the mental process to expedite the process will cause the information to be excluded from the message, therefore increasing exformation. As we fragment knowledge and lose a sense of wisdom, what happens to us psychologically as individuals and as a group (Spaulding 2002)?”

Regardless of the drawbacks of electronic mail, it is a tool society is quickly adopting into many cultures.  The ability to communicate globally without the usual restrictions of time and space has made this tool very popular.  The use of the tool has become so prevalent that a backlash has occurred where professionals focus on the medium, not the message.

 

 

 

 


Appendix Section

 

 Appendix A – Electronic Mail Survey

 

Population

Passengers on the Long Island Rail Rod (LIRR), Respondents were Westbound morning commuters or Eastbound evening commuters.

Sample Frame

Any adult.

Sample

Respondents to ad hoc requests.  Approximately 90 respondents is the survey goal.

Method

Self-Administered Questionnaire.  Surveys will be confidential and anonymous.  Surveys will be administered on the railroad.

Motivation

Is the use of electronic mail contributing to Information overload?

Feasibility

This research team believes that a survey of this nature is feasible.  Cost will be relatively low.  The response rate is estimated to be 100%.

Definition of Key Terms

Adult: Any one over aged 18.

 

Assumption

Adult has familiarity or experience with the electronic mail.

Importance

This issue has an impact on how members of society communicate with one another.

 

 

Research Question

 

Does the proliferation of electronic mail contribute to information overload?

 

Independent Variables

If an adult is a user of electronic mail?

 

Dependent Variables

The volume of electronic does or does not contribute to information overload.

 

Null Hypothesis

Electronic mail does not contribute to information overload.

 

 

 


Questionnaire # ______

 

 

 

All responses are anonymous and will be kept confidential.

 

 

 

 

Question

 

 

Response

 

 

 

 

1.

Does the electronic mail contribute to information overload?

 

Yes               No

2.

Do you access your professional electronic mails from home?

 

Yes               No          Not applicable

3.

# of e-mail accounts?

 

Enter actual #:

4.

Do you like the idea of a 'No electronic mail day'?

 

Yes               No

5.

# of electronic mails you deleted without reading per day?

 

Enter actual #:

6.

Do you view the task of reading electronic mail as a:

 

 

Ø      Chore

Ø      Benefit

7.

Do you mentally calculate the number of electronic mail you will receive when you are not in the workplace?

 

Yes               No          Not applicable

8.

Electronic mail is valuable mode of communications: 

 

 

Ø      Strongly Agree

Ø      Agree

Ø      Neither Agree or Disagree 

Ø      Disagree

Ø      Strongly Disagree

 

 

 

 

 

 

The questions asked below will allow data analysis by categories.

 

 

(Circle your answer)

9.

Your gender.

 

 

Female        Male

10.  

Your age group.

 

Ø      (18 – 35)

Ø      (36 – 45)

Ø      (46 – 55)

Ø      (Over 55)

 

11.

Area of professional work:

 

Ø      Government

Ø      Education

Ø      Corporate

Ø      Other

 

12.

Number of children or dependents?

 

Ø      (0)

Ø      (1-3)

Ø      (4-6)

Ø      (Over 6)

 

13.

Ethnicity.

 

Ø      African American

Ø      Asian

Ø      Caucasian

Ø      Hispanic

Ø      Other (Please specify) ________________

 

 

14.

Your highest level of education?

 

 

 

Ø      High school

Ø      Bachelor Degree

Ø      Masters Degree

Ø      Doctorate

Ø      Other (Please specify) ________________

 

 


Appendix B – Frequency Distribution

 

Frequency Table for Q1: Does the electronic mail contribute to information overload?

                                                                                    Cumulative     Cumulative

         Q1_CONTRIB              Frequency      Percent           Frequency      Percent

                        No                   12                    36.36              12                    36.36

Yes                21                     63.64              33                    100.0

 

 

 

Frequency Table for Q2: Do you access your professional electronic mails from home?                                                                                                                                                                                                                            Cumulative     Cumulative

         Q2_ACCESS      Frequency              Percent           Frequency      Percent

              No                             14                    42.42              14                    42.42

              Yes                            19                    57.58              33                    100.0

 

 

 

Frequency Table for Q3: # of e-mail accounts?

                                                                                    Cumulative     Cumulative

         Q3_ACCOUNT     Frequency             Percent           Frequency      Percent

             0                     1                      3.03                1                      3.03

             1                     8                      24.24              9                      27.27

             2                                 15                    45.45              24                    72.73

             3                     4                      12.12              28                    84.85

             4                     3                      9.09                31                    93.94

             5                     1                      3.03                32                    96.97

             7                     1                      3.03                33                    100.0

 

 

Frequency Table for Q4: Do you like the idea of a 'No electronic mail day'?                                                                                                                                        Cumulative               Cumulative

         Q4_NO_EMAI              Frequency      Percent           Frequency       Percent

                                    1                      3.03                1                      3.03

                        N                     17                    51.52              18                    4.55

                        Y                      15                    45.45              33                    100.0

 

 

 Frequency Table for Q5:    # of electronic mails you deleted without reading per day?

                                                                                    Cumulative     Cumulative

         Q5_NOREADD            Frequency      Percent   Frequency             Percent

                        0                      7          21.21              7                      21.21

                                    1                      1          3.03                8                      24.24

                                    4                      1          3.03                9                      27.27

                                    6                      1          3.03               10       30.3

                                    10                    8          24.24              18                    54.55

                                    15                    2          6.06                20                    60.61

                                    20                    3          9.09                23       69.7

                                    25                    1          3.03                24                    72.73

                                    30                    3          9.09                27                    81.82

                                    60                    1          3.03                28                    84.85

                                    100                2           6.06                30                    90.91

                                    125                1           3.03                31                    93.94

                                    200                1           3.03                32                    96.97

                                    500                1           3.03                33                    100.0

 

               

Frequency Table for Q6: Do you view the task of reading electronic mail as a:                                                                                                                                               Cumulative               Cumulative

         Q6_CHORE       Frequency   Percent           Frequency      Percent

                                                3                      9.09                            3          9.09

             Benefit                       17                    51.52                          20        60.61

             Chore                        13                    39.39                          33        100.0

 

 

Frequency Table for Q7: Do you mentally calculate the number of electronic mail you will receive when you are not in the workplace?

                                                                                    Cumulative     Cumulative

         Q7_MENTAL      Frequency               Percent           Frequency      Percent

              No                             17                    51.52              17                    51.52

             Yes                             16                    48.48              33                    100.0

 

 

 

Frequency Table for Q8: Electronic mail is valuable mode of communications:

                                                                                    Cumulative     Cumulative

         Q8_VALUE                  Frequency      Percent           Frequency      Percent

Strongly Agree                      17        51.52              17                    51.52

           Agree                                      16        48.48              33                    100.0

 

 

Frequency Table for Q9: Gender

                                                                                    Cumulative     Cumulative

         Q9_GENDER               Frequency      Percent           Frequency      Percent

                      F                        10                    30.3                10       30.3

                        M                     23                    69.7                33                    100.0

 

 

Frequency Table for Q10: AGE

                                                                                    Cumulative     Cumulative

         Q10_AGE        Frequency      Percent           Frequency      Percent

             18-35                         12                    36.36              12                    36.36

             36-45                         14                    42.42              26                    78.79

             46-55             5                      5.15                31                    93.94

             Over 55                     2                      6.06                33                    100.0

 

 

Frequency Table for Q11:  Area of professional work                                                                                                                                             Cumulative     Cumulative

         Q11_PROFES             Frequency      Percent           Frequency      Percent

             Other                          4                      12.12              4                      12.12

             Government           2                         6.06                6                      18.18

             Education               3                        9.09                9                      27.27

             Corporate               24                      72.73              33                    100.0

 

 

Frequency Table for Q12: Number of Dependents

                                                                                    Cumulative     Cumulative

         Q12_DEPEND     Frequency             Percent           Frequency      Percent

             No Response           3                      9.09                3                      9.09

             0                     8                      24.24              11                    33.33

             1-3                             22                    66.67              33                    100.0

 

 

Frequency Table for Q13: Ethnic Background

                                                                                    Cumulative     Cumulative

         Q13_ETHNIC               Frequency      Percent           Frequency      Percent

            African American                    2          6.06                2                      6.06

            Asian                                       6          18.18              8                      24.24

Caucasian                  22        66.67              30                    90.91

Hispanic                                  1          3.03                31                    93.94

Other                                       2          6.06                33                    100.0

 

 

Frequency Table for Q14: Level of Education

                                                                                    Cumulative     Cumulative

Q14_EDUCAT          Frequency      Percent           Frequency      Percent

High school                             4          12.12              4                      12.12

Bachelor Degree                     14        42.42              18                    54.55

Masters Degree                      13        39.39              31                    93.94

Doctorate                                1          3.03                32                    96.97

Other                                       1          3.03                3                      100.0


 

Resources

 

 

Anonymous.  http://www.mailbase.ac.uk/docs/overload/tsld002.htm. What causes Information overload? Last site visit 05/19/2002.

 

Boyer, Ernest L. Conference on Intellectual Property Rights and the Arts: The Impact of New Technologies”.  http://mitpress2.mit.edu/e-journals/Leonardo/isast/spec.projects/boyer.html. Last visit: 05/18/2002.

 

Berst, Jesse.  “End Inbox Blues: Common-Sense Ways to Control Electronic mail Overload. July 5th, 2000.  http://www.zdnet.com/anchordesk/stories/story/0,10738,2597972,00.html. Last visit: 05/21/2002.

 

 

Eppler, Martin.  Definition Information Overload (1999).  http://www.knowledgemedia.org/netacademy/glossary.nsf/kw_id_all/845. Last visit: 05/18/2002.

 

 

Jones International. Norbert Wiener (1894 - 1964). http://www.digitalcentury.com/encyclo/update/wiener.html. Last visit: 05/18/2002.

 

 

Maes, Pattie. Agents that Reduce Work and Information Overload. http://agents.www.media.mit.edu/people/pattie/CACM-94/CACM-94.p1.html.  Last visit: 05/03/2002.

 

Nelson, Mark R.  We Have the Information You Want, But Getting It Will Cost You: Being Held Hostage by Information Overload. http://www.acm.org/crossroads/xrds1-1/mnelson.html. Last visit: 05/03/2002.

 

Kirsh, David. A Few Thoughts on Cognitive Overload. http://icl-server.ucsd.edu/~kirsh/Articles/Overload/published.html. Last visit: 05/03/2002.

 

Kostelanetz, Richard. Understanding McLuhan (In Part) January 29, 1967. http://www.nytimes.com/books/97/11/02/home/mcluhan-magazine.html. (Last site review: 05/19/2002).

 

Lashkari, Y., Metral, M. and Maes, P. Collaborative Interface Agents. In: Proceedings of the National Conference on Artificial Intelligence, 1994.

 

Losee, Robert M..  “Information overload, internet filtering agents, e-mail filtering, information filtering, user modeling, routing, ranking electronic mail Minimizing Information Overload: the Ranking of Electronic Messages.”  Journal of Information Science, 15, 1989, p. 179-189.

 

Machlup, Fritz., Mansfield, Una. “The Study of Information: Interdisciplinary Messages.”  John Wiley and Sons.  New York. Date unkown.

 

Maes, Pattie. Agents that Reduce Work and Information Overload. http://agents.www.media.mit.edu/people/pattie/CACM-94/CACM-94.p1.html.  Last visit: 05/03/2002.

 

Naisbitt, John. Megatrends. New York: Warner Books. 1982. (This book is out of print, but you might be interested in a newer version: Megatrends 2000 by the same author.)

 

Nelson, Mark R.  We Have the Information You Want, But Getting It Will Cost You: Being Held Hostage by Information Overload. January 12th, 2001.  http://www.acm.org/crossroads/xrds1-1/mnelson.html. Last visit: 05/03/2002.

 

Norretranders, Tor.  The User Illusion: Cutting Consciousness Down to Size.  Penguin Books.  New York. 1998.

 

Roach, Stephen. “Technology traps us into working 24/7.Listen to Stephen Roach of Morgan Stanley Dean Witter.”  http://www.softpanorama.org/Social/overload.shtml. Last visit: 05/22/2002.

 

Spaulding, Amy, Interview by Thomas Virgona, phone, June 24th, 2002.

 

Underwood, Mick.  “The Shannon-Weaver Model”. http://www.cultsock.ndirect.co.uk/MUHome/cshtml/index.html. Last visit: 05/22/2002.

 

Wilson T.D. Information Overload (06/01/01). http://informationr.net/tdw/publ/ppt/overload/.  Last visit of website 05/20/2002.