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Empirical Study of Balance Between Phone and Instant Messenger Conversations Ratko Jagodic Ken Dallmeyer Eugene Khokhlov Motivation 59% percent of Americans use Instant Messaging 90% of people 13 thru 21 49% of people 55 and over 27% use it at work
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Empirical Study of Balance Between Phone and Instant Messenger Conversations Ratko Jagodic Ken Dallmeyer Eugene Khokhlov
Motivation • 59% percent of Americans use Instant Messaging • 90% of people 13 thru 21 • 49% of people 55 and over • 27% use it at work • IM eliminates the fear of face to face conversation • Some people save a lot of money by moving their conversation to IM Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Previous Work • IM are particularly useful in mixed-sex communication - Schianno et al. (2002) • 39% of adolescents had mixed-gender conversations on IM as opposed to 12.5% that used the phone - Boneva et al. (2004) • Frequent users had more turns (switches) than infrequent users on IM – Isaacs et al. (2002) Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Goals • To quantitatively compare the phone and IM conversations • For both phone and IM: • number of switches per minute • balance between users (time-wise) Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Hypothesis • The number of switches per minute is higher for phone conversations • The balance of conversation is even for IM, but on average the phone conversation is dominated by one person Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Procedure • Collected 27 conversations from MSM and AIM with permission of the participants • Collected 18 phone conversations with a phone recorder with permission of the speakers Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Subjects • IM – Ratko (MSN) and Eugene (AIM) • Ages 18 – 56, male and female • Phone – Ken and his family • Ages 11 – 54, male and female • No conversations were between the three of us Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Data Analysis • IM • A Python program was written to parse the conversation logs • Phone • A tedious process of writing the time at each switch • Excel was used to process the phone data Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Results • Balance • 62% to 38% IM • 60% to 40% Phone • Mean Number of Switches per Minute • 2.37 IM • 17.18 Phone Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Results - Balance • P value for the conversation balance is .66 (bad) Meaning we cannot say much about it. Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Results – Switches • P value for the number of switches is: • < .001 (good) Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Conclusion • Balance • On average the balance for phone and IM is similar • 60%-40% (phone) vs. 62%-38% (IM) • However our P-value of .66 says that our data is inconclusive Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Conclusion • Switches Per Minute • As expected the number of switches per minute was greater in phone conversations than IM • Mean: 2.37 (IM) vs. 17.18 (phone) • The p-value < .01 • We are pretty confident that there is a difference in switches per minute between phone and IM conversations Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Issues We Encountered • This is a qualitative study that from which we tried to get quantitative results • Time inconsistencies • Pauses • Interruptions • Typing speed • Talking at the same time • Utterances – “umms”, “yeah”, “uh huh”, etc. • All subjects are different from each other Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Issues We Encountered • Not nearly enough data points to determine balance • What takes so long in IM can be done much quicker on the phone – some normalization needs to be applied Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov
Questions? The End http://www.washingtonpost.com/wp-dyn/articles/A54261-2004Sep1.html Ratko Jagodic, Ken Dallmeyer, Eugene Khokhlov