Cleaning house or quiet quitting? Large-scale analysis of account deletion behaviour on Tumblr

Figures & data

Table 1. The independent variables for data analysis.

Feature	Measure Formula	Explanation
Deleted posts	$\mathrm{De}{l}_i=\sum _j(\mathrm{de}{l}_i(j))$	The number of posts a blog i deleted during its trial period.
Deleted followees	$\mathrm{CFi}{n}_i=\frac{\sum _j^{\mathrm{Fi}{n}_i}\mathrm{CC}(j)}{\mathrm{Fi}{n}_i}$	The proportion of blogs which were followed by blog i and became complete churners in its trial period.
Deleted followers	$\mathrm{CFou}{t}_i=\frac{\sum _j^{\mathrm{Fou}{t}_i}\mathrm{CC}(j)}{\mathrm{Fou}{t}_i}$	The proportion of blogs that follow blog i and became complete churners in its trial period.
Reciprocity	$\mathrm{Re}{c}_i=\frac{\mathrm{Fou}{t}_i\cup \mathrm{Fi}{n}_i}{\mathrm{Fou}{t}_i\cap \mathrm{Fi}{n}_i}$	Reciprocity measures the mean proportion of reciprocal relationships a blog i has in its trial period.
Social reactiveness	$P{R}_i=\frac{p_i^D\ast (R{e}_i^D>1)/|D|}{p_i^D/|D|}$	The ratio of the average number of posts a blog i has posted on days when it received at least one reblog ($R{e}_i^D$), to the average number of posts it posted on days when it received no reblogs.
Activity	$A{c}_i=\sum _j\frac{|p_i|}{|D|}$	Activity measures the mean number of daily posts blog i has posted or shared during the trial period.
Followers	$I{n}_i=\frac{1}{|D|}\sum _{d\in D}\mathrm{Fi}{n}_i(d)$	The mean number of followers blog i has during its trial period.
Followees	$\mathrm{Ou}{t}_i=\frac{1}{|D|}\sum _{d\in D}\mathrm{Fou}{t}_i(d)$	The mean number of daily followees blog i during the trial period.
Originality	$\mathrm{Ori}{g}_i=\frac{1}{|D|}\sum _{d\in D}\frac{p_i(d)}{r{e}_i(d)}$	The mean proportion of original posts blog i has posted of all posts it posted during its trial period.

Notes: The table includes the name, definition, and description of each measure. We define the posts by a user i in day D as $p_i^D$ and the reblogs as $\mathrm{Re}(p_i^D)$. The features are grouped according to research questions and control variables

Figure 1. Distribution of in-degree and out-degree of blogs. (a) The distribution of the number of followees (out-degree) per account and (b) The distribution of the number of followers (in-degree) per account.

Two graphs presenting the distribution of creation year and deleted posts per each blog.

Figure 2. Distribution of creation year and deleted posts. (a) Distribution of creation year and (b) Distribution of deleted posts.

Table 2. Proportion of deleted accounts in different levels of activity.

Use level	Deleted	Not deleted	Total	Proportion
Less active	2,839	929,592	932,431	0.0030
More active	18,273	3,530,149	3,548,422	0.0051
Total	21,112	4,459,741	4,480,853	0.0047

Notes: Less active users had at least one month in which they were not active during the four-month study period. More active users were active at least once every month in that period.

Table 3. Logistic regression models for account deletion.

Feature	Control Model				Full model
	Coeff	Std. err.	Z	$P>|z|$	Coeff	Std. err.	Z	$P>|z|$
Intercept	−8.25	0.04	−195.59		−101.17	5.69	−17.79	<0.001
Predictor Variables
Deleted posts					37.85	0.85	44.36	<0.001
Deleted followers					0.79	0.08	9.87	<0.001
Deleted followees					92.57	5.68	16.28	<0.001
Social reactiveness					−22.98	4.52	−5.08	<0.001
Reciprocity					2.21	0.07	29.48	<0.001
Control Variables
Created date	3.41	0.05	68.50	<0.001	3.78	0.05	71.42	<0.001
Activity	4.09	0.63	6.47	<0.001	3.88	0.68	5.69	<0.001
Followers	6.27	1.40	4.47	<0.001	5.76	1.66	3.48	<0.001
Followees	0.08	0.14	0.59	0.55	−0.22	0.15	−1.47	0.14
Originality	0.49	0.03	18.69	<0.001	0.44	0.03	16.23	<0.001
NSFW Flag	0.31	0.02	18.68	<0.001	0.45	0.02	25.79	<0.001

Notes: Two models were tested to evaluate the goodness of fit: a control model comprising only control features and a full model incorporating both independent predictors and control variables.

Figure 3. The four segments, each with its centroid value of the five variables. The ‘never followed’ users are not presented because they do not have centroid values.

The centroid values of different properties according to segment.

Table 4. The contingency of the number of blog deleters categorised by segment, along with the results of post-hoc hypothesis tests.

Segment	Contingency		Delete prob	Adjusted Pearson Residual
	Non-deleters	Deleters		Non-deleters	Deleters
Long term followed	1,973,185	4652	0.23%	−64.835	64.835
Recently registered	1,894,681	12525	0.65%	49.377	−49.377
Original blogs	471,522	3251	0.68%	22.729	−22.729
Active most-followed	83,130	431	0.51%	1.902	−1.902
Never followed	37,223	253	0.67%	5.789	−5.789

Table 5. Logistic regression models for each cluster.

Cluster	Long term followed	Recently registered	Active most-followed	Original	Never followed
Intercept	−362.2 (25.95)***	−36.76 (5.62)***	15.26 (10.67)	0.89 (3.99)	−45.05 (50.65)
Deleted posts	29.97 (0.89)***	97.43 (2.63)***	19.22 (3.22)***	26.32 (4.11)***	202.95 (299.67)
Deleted followees	356.48 (25.98)***	31.51 (5.63)***	−20.72 (10.69)	−6.21 (4.00)	39.39 (50.75)
Deleted followers	3.60 (0.32)***	1.49 (0.09)***	1.26 (0.43)**	1.18 (0.17)***	−20.82 (18.26)
Social reactiveness	−7.37 (17.94)	2.77 (8.84)	−21.50 (8.31)**	14.84 (19.50)	−589.31 (480.08)
Reciprocity	−1.46 (0.23) ***	2.10 (0.10) ***	1.83 (0.65) **	1.97 (0.14) ***	3.28 (1.37)

Figure A1. A screenshot of the user interface on Tumblr for account deletion. The interface is displayed to users after clicking the settings page's ‘Delete Account’ link. The UI asks them to authenticate to complete the permanent account deletion process, click the ‘Nevermind’ link, or click the browser's ‘back’ button to cancel.

Figure A2. Distribution of deleted followees and deleted followers. (a) The distribution of the number of deleted followees and (b) The distribution of the number of deleted followers

Two graphs presenting distributions of deleted followees and deleted followers.

Figure A3. The distribution of social reactiveness.

A graph presenting the distribution of social reactiveness.

Figure A4. The Sum of Squares Error (SSE) is plotted against the number of clusters.

A plot for the sum of squares error for the number of clusters.

Figure A5. Distribution of users' originality and NSFW Flag. (a) The distribution of the users' originality: the proportion of original content and (b) NSFW Flag distribution. 1 -- blogs with adult content, 0- blogs without adult content.

Two graphs presenting distributions of users' originality and NSFW Flag.

Table A1. Feature stability over the four-month study period, which presents the mean and variability of each feature.

Feature	Mean	Variance
Activity	13.37	1.26
Originality	0.12	0.0012
Activity for days without feedback	7.21	1.59
Activity for days with feedback	10.35	0.934
Deleted followers	0.015	0.00036
Deleted follows	0.018	0.00013
Reciprocity	24.03	0.0011

Notes: All variables exhibit relatively low variability to the average. The table presents the mean and variance of the main variable during the study's period.

Table A2. The goodness of fit for the logistic regression models by segments was evaluated using a deviance test between each model and the 0-Model.

Model	Deviance	${\mathrm{\Xi }}^2$	DF	P value
0-Model	201,201
Full model	191,210	9990	11	<0.001
Model with only control variables	194,242	6959	6	<0.001

Table A3. Clusters centroid values and interpretation.

Cluster	Activity	Created date	In-degree	Out-degree	Originality
Long term followed	−0.0564	−0.8396	0.1063	0.2614	−0.3316
Recently registered	−0.1211	0.8094	−0.1196	−0.2489	−0.3128
Original	−0.2876	0.2047	0.0059	−0.2456	2.6955
Active most-followed	5.7323	0.2368	0.1794	0.8873	−0.3273

Notes: The table includes only the clusters that resulted from the K-means clustering results, so it does not include the ‘Never followed blogs’ cluster.