1336|37 277301|277 213499 1251.42 (a)Number of conversations()Conversation duration 1.431 1.4 two-person conversations during June 2006. (a) Percentage of conversations among users of differ- ength in seconds umber of exchanged messages per conversation;(d) number of exchanged messages (c) Messages per conversation (d) Messages per unit time per minute of conversation Figure 6: Communication characteristics of users by reported age. We plot age vs. age and the color(z- serve a similar phenomenon when plotting the average num- axis )represents the intensity of communication ber of exchanged that fica. mi, displayed in Figure 6(c). Again, we find lder people exchange more messages, and we observe priorities arrive and wait until all tasks with higher priority a dip for ages 25-45 and a slight peak for ages 15-25. Fig- e addressed. This model generates a task waiting time ure 6(d)displays the number of exchanged messages per un distribution described by a power-law with exponent -1.5. time; for each age pair, (a, 6), we measure cao 2ieca. Here, we see that younger people have faster-paced dialogs 5. COMMUNICATION DEMOGRAPHICS while older people exchange messages at a slower Next we examine the interplay of communication and user We note that the younger population (ages 10-35 )are demographic attributes, i. e, how geography, location, age strongly biased towards communicating with people of a and gender influence observed communication patterns similar age(diagonal trend in Figure 6(a)), and that users who report being of ages 35 years and above tend to com- 5.1 Communication by age municate more evenly across ages(rectangular pattern in We sought to understand how communication among peo- Fig. 6(a)). Moreover, older people have conversations of the ple changes with the reported ages of participating users longest durations, with a"valley"in the duration of conver Figures 6(a)-(d)use a heat-map visualization to commu- sations for users of ages 25-35. Such a dip may represent nicate properties for different age-age pairs. The rows and shorter, faster-paced and more intensive conversations asso- columns represent the ages of both parties participating, and ciated with work-related communications. versus more ex- the color at each age-age cell captures the logarithm of the tended, slower, and longer interactions associated with social value for the pairing. The color spectrum extends from blue Discours low value) through green, yellow, and onto red(the highest value). Because of potential misreporting at very low and 5.2 Communication by gender high ages, we concentrate on users with self-reported ages that fall bet ween 10 and 60 years s We report on analyses of properties of pairwise communi cations as a function of the self-reported gender of users in Let a tuple(ai, bi, di, mi)denote the ith conversation conversations in Table 1. Let Cg, h=I(gi, hi, di, mi): gi the entire dataset that occurred among users of ages ai g Ahi= h denote a set of conversations where the two par and bi. The conversation had a duration of di seconds ticipating users are of genders g and h. Note that g takes 3 ring which mi messages were exchanged. Let Ca, b= possible values: female, male, and unknown(unreported) I(ai, bi, di, mi): ai= aA bi= b denote a set of all con- Table 1(a)relays Cg, h for combinations of genders g and versations between users of ages a and b, respectively. h. The table shows that approximately 50% of conversations Figure 6(a)shows the number of conversations among peo. occur between male and female and 40% of the conversations ple of different ages. For every pair of ages(a, b) the color occur among users of the same gender(20% for each).A indicates the size of set Ca.b. i.e., the number of different small number of conversations occur between people who conversations between users of ages a and b. We note that id not reveal their gender s the notion of a conversation is symmetric, the plots ar Similarly, Table 1(b)shows the average conversation length symmetric. Most conversations occur between people of ages seconds, broken down by the gender of conversant, com- 10 to 20. The diagonal trend indicates that people tend to puted as TCoh Ziece n di. We find that male-male conver alk to people of similar age. This is true especially for age sations tend to be shortest, lasting approximately 4 min- groups between 10 and 30 years. We shall explore this ob- utes. Female-female conversations last 4.5 minutes on the servation in more detail in Section 6 rsations have the longest du- Figure 6(b)displays a heat map for the average conver- rations, taking more than 5 minutes on average. Beyond sation duration, computed as We note aking place over longer periods of time, more messages are that older people tend to have longer conversations. We ob exchanged in female-male conversations. Table 1(c) lists10 20 30 40 50 60 10 15 20 25 30 35 40 45 50 55 60 10 20 30 40 50 60 10 15 20 25 30 35 40 45 50 55 60 (a) Number of conversations (b) Conversation duration 10 20 30 40 50 60 10 15 20 25 30 35 40 45 50 55 60 10 20 30 40 50 60 10 15 20 25 30 35 40 45 50 55 60 (c) Messages per conversation (d) Messages per unit time Figure 6: Communication characteristics of users by reported age. We plot age vs. age and the color (z￾axis) represents the intensity of communication. priorities arrive and wait until all tasks with higher priority are addressed. This model generates a task waiting time distribution described by a power-law with exponent −1.5. 5. COMMUNICATION DEMOGRAPHICS Next we examine the interplay of communication and user demographic attributes, i.e., how geography, location, age, and gender influence observed communication patterns. 5.1 Communication by age We sought to understand how communication among peo￾ple changes with the reported ages of participating users. Figures 6(a)-(d) use a heat-map visualization to commu￾nicate properties for different age–age pairs. The rows and columns represent the ages of both parties participating, and the color at each age–age cell captures the logarithm of the value for the pairing. The color spectrum extends from blue (low value) through green, yellow, and onto red (the highest value). Because of potential misreporting at very low and high ages, we concentrate on users with self-reported ages that fall between 10 and 60 years. Let a tuple (ai, bi, di, mi) denote the ith conversation in the entire dataset that occurred among users of ages ai and bi. The conversation had a duration of di seconds during which mi messages were exchanged. Let Ca,b = {(ai, bi, di, mi) : ai = a ∧ bi = b} denote a set of all con￾versations between users of ages a and b, respectively. Figure 6(a) shows the number of conversations among peo￾ple of different ages. For every pair of ages (a, b) the color indicates the size of set Ca,b, i.e., the number of different conversations between users of ages a and b. We note that, as the notion of a conversation is symmetric, the plots are symmetric. Most conversations occur between people of ages 10 to 20. The diagonal trend indicates that people tend to talk to people of similar age. This is true especially for age groups between 10 and 30 years. We shall explore this ob￾servation in more detail in Section 6. Figure 6(b) displays a heat map for the average conver￾sation duration, computed as 1 |Ca,b| P i∈Ca,b di. We note that older people tend to have longer conversations. We ob- (a) U F M U 1.3 3.6 3.7 F 21.3 49.9 M 20.2 (b) U F M U 277 301 277 F 275 304 M 252 (c) U F M U 5.7 7.1 6.7 F 6.6 7.6 M 5.9 (d) U F M U 1.25 1.42 1.38 F 1.43 1.50 M 1.42 Table 1: Cross-gender communication, based on all two-person conversations during June 2006. (a) Percentage of conversations among users of differ￾ent self-reported gender; (b) average conversation length in seconds; (c) number of exchanged messages per conversation; (d) number of exchanged messages per minute of conversation. serve a similar phenomenon when plotting the average num￾ber of exchanged messages per conversation, computed as 1 |Ca,b| P i∈Ca,b mi, displayed in Figure 6(c). Again, we find that older people exchange more messages, and we observe a dip for ages 25–45 and a slight peak for ages 15–25. Fig￾ure 6(d) displays the number of exchanged messages per unit time; for each age pair, (a, b), we measure 1 |Ca,b| P i∈Ca,b mi di . Here, we see that younger people have faster-paced dialogs, while older people exchange messages at a slower pace. We note that the younger population (ages 10–35) are strongly biased towards communicating with people of a similar age (diagonal trend in Figure 6(a)), and that users who report being of ages 35 years and above tend to com￾municate more evenly across ages (rectangular pattern in Fig. 6(a)). Moreover, older people have conversations of the longest durations, with a “valley” in the duration of conver￾sations for users of ages 25–35. Such a dip may represent shorter, faster-paced and more intensive conversations asso￾ciated with work-related communications, versus more ex￾tended, slower, and longer interactions associated with social discourse. 5.2 Communication by gender We report on analyses of properties of pairwise communi￾cations as a function of the self-reported gender of users in conversations in Table 1. Let Cg,h = {(gi, hi, di, mi) : gi = g ∧hi = h} denote a set of conversations where the two par￾ticipating users are of genders g and h. Note that g takes 3 possible values: female, male, and unknown (unreported). Table 1(a) relays |Cg,h| for combinations of genders g and h. The table shows that approximately 50% of conversations occur between male and female and 40% of the conversations occur among users of the same gender (20% for each). A small number of conversations occur between people who did not reveal their gender. Similarly, Table 1(b) shows the average conversation length in seconds, broken down by the gender of conversant, com￾puted as 1 |Cg,h| P i∈Cg,h di. We find that male–male conver￾sations tend to be shortest, lasting approximately 4 min￾utes. Female–female conversations last 4.5 minutes on the average. Female–male conversations have the longest du￾rations, taking more than 5 minutes on average. Beyond taking place over longer periods of time, more messages are exchanged in female–male conversations. Table 1(c) lists