#1Q1 2019 Earnings Report#2Non-GAAP Financial Measures In addition to U.S. GAAP financials, we have supplementally provided certain non-GAAP financial measures. These non-GAAP financial measures are in addition to, and not a substitute for or superior to, measures of financial performance prepared in accordance with U.S. GAAP. As required by Regulation G, we have provided a reconciliation of those measures to the most directly comparable GAAP measures in the Appendix. A Note About Metrics We define monetizable daily active usage or users (mDAU) as Twitter users who logged in or were otherwise authenticated and accessed Twitter on any given day through Twitter.com or Twitter applications that are able to show ads. Average mDAU for a period represents the number of monetizable DAU on each day of such period divided by the number of days for such period. Changes in mDAU are a measure of changes in the size of our daily logged in or otherwise authenticated active user base. To calculate the year-over-year change in mDAU, we subtract the average mDAU for the three months ended in the previous year from the average mDAU for the same three months ended in the current year and divide the result by the average mDAU in the previous year. Additionally, our calculation of mDAU is not based on any standardized industry methodology and is not necessarily calculated in the same manner or comparable to similarly-titled measures presented by other companies. mDAU are calculated in the same manner as DAU used in calculations for Change in DAU presented in previous periods. We define monthly active usage or users (MAU) as Twitter users who logged in or were otherwise authenticated and accessed Twitter through our website, mobile website, desktop or mobile applications, SMS or registered third-party applications or websites in the 30-day period ending on the date of measurement. Average MAU for a period represent the average of the MAU at the end of each month during the period. Certain metrics also include users that access Twitter through applications that automatically contact our servers for regular updates with no discernible user-initiated action involved, which we refer to as third-party auto-polling MAU. This activity causes our system to count MAUSs associated with such applications as active users on the day or days such contact occurs. As of December 31, 2018, fewer than 8.5% of MAUS may have been third-party auto-polling MAU. Third-party auto-polling does not apply to mDAU as mDAU does not include users accessing Twitter through third-party applications. 2#3A Note About Metrics (continued) The numbers of active users presented in our earnings materials are based on internal company data. While these numbers are based on what we believe to be reasonable estimates for the applicable period of measurement, there are inherent challenges in measuring usage and user engagement across our large user base around the world. Furthermore, our metrics may be impacted by our information quality efforts, which are our overall efforts to reduce malicious activity on the service, inclusive of spam, malicious automation, and fake accounts. For example, there are a number of false or spam accounts in existence on our platform. We have performed an internal review of a sample of accounts and estimate that the average of false or spam accounts during the first quarter of 2019 represented fewer than 5% of our mDAU and MAU during the quarter. The false or spam accounts for a period represents the average of false or spam accounts in the samples during each monthly analysis period during the quarter. In making this determination, we applied significant judgment, so our estimation of false or spam accounts may not accurately represent the actual number of such accounts, and the actual number of false or spam accounts could be higher than we have estimated. We are continually seeking to improve our ability to estimate the total number of spam accounts and eliminate them from the calculation of our active users, and have made improvements in our spam detection capabilities that have resulted in the suspension of a large number of spam, malicious automation and fake accounts. We intend to continue to make such improvements. After we determine an account is spam, malicious automation or fake, we stop counting it in our mDAU, MAU or related metrics. Additionally, we rely on third-party SMS aggregators and mobile carriers to deliver SMS messages to certain of our users when we send our SMS messages to such accounts. If, however, we are notified of material deliverability issues because of, for example, infrastructure issues at the service-provider level or governmental restrictions based on content, we do not include the affected users in MAUS. We also treat multiple accounts held by a single person or organization as multiple users for purposes of calculating our active users because we permit people and organizations to have more than one account. Additionally, some accounts used by organizations are used by many people within the organization. As such, the calculations of our active users may not accurately reflect the actual number of people or organizations using our platform. In addition, our data regarding user geographic location for purposes of reporting the geographic location of our MAU and mDAU is based on the IP address or phone number associated with the account when a user initially registered the account on Twitter. The IP address or phone number may not always accurately reflect a user's actual location at the time such user engaged with our platform. For example, a mobile user may appear to be accessing Twitter from the location of the proxy server that the user connects to rather than from a user's actual location. We regularly review and may adjust our processes for calculating our internal metrics to improve their accuracy. Our measures of user growth and user engagement may differ from estimates published by third parties or from similarly-titled metrics of our competitors due to differences in methodology. 3#4Monetizable Daily Active Usage (quarterly average, millions) International US Y/Y Rate 120 94 26 Q1'18 10% 122 96 26 Q2'18 11% 124 98 26 Q3'18 9% 126 99 27 Q4'18 9% 134 105 28 Q1'19 (1) 11% (1) Please note that the sum of US mDAU and International mDAU does not add up to total mDAU in Q1'19 above due to rounding. (2) Please note that the sum International Y/Y and US Y/Y does not add up to Worldwide Y/Y in the above due to rounding. +14m² WW Y/Y +11m Int'l Y/Y +2m US Y/Y 4#5Monthly Active Usage (quarterly average, millions) International US 336 267 69 Q1'18 335 267 68 Q2'18 326 259 67 Q3'18 321 255 66 Q4'18 330 262 68 Q1'19 -6m WW Y/Y -5m Int'l Y/Y -1m US Y/Y 5#6Total Revenue ($, millions) Data Licensing & Other Revenue Advertising Revenue % Intl $665 $90 $575 Q1'18 48% $711 $109 $601 Q2'18 (3) 48% $758 $108 $650 Q3'18 44% $909 $117 $791 Q4'18 (3) 44% $787 $107 $679 Q1'19 (3) 45% (3) Please note that the sum of Data Licensing and Other Revenue and Advertising Revenue does not add up to Total Revenue in the above due to rounding. +18% Total Y/Y +20% Data Licensing & Other Y/Y +18% Advertising Y/Y 6#7Advertising Revenue by Geography ($, millions) International US $575 $287 $288 Q1'18 $601 $308 $293 Q2'18 $650 $302 $348 Q3'18 $791 $366 $425 Q4'18 $679 $317 $363 Q1'19 (4) (4) Please note that the sum of International Advertising Revenue and US Advertising Revenue does not add up to Total Advertising Revenue in the above due to rounding. +18% Total Y/Y +10% Int'l Y/Y +26% US Y/Y 7#8GAAP Operating Income ($, millions) $75 Q1'18 Operating 11% Margin $80 Q2'18 11% $92 Q3'18 12% $207 Q4'18 23% $94 Q1'19 12% +25% Y/Y 8#9GAAP Net Income (5) ($, millions) GAAP Net Margin $61 Q1'18 9% $100 Q2'18 14% $789 Q3'18 104% $255 Q4'18 28% $191 Q1'19 24% (5) Our net income includes the following one-time benefits for income taxes: Q2'18, Q3'18, and Q4'18 include the realization of deferred tax assets in the US and Brazil of $42 million, $683 million, and $120 million, respectively. Q1'19 includes the impact of $124 million to establish a deferred tax asset for corporate structuring for certain geographies. +213% Y/Y 9#10Appendix#11Adjusted EBITDA Reconciliation ($, thousands) Net Income Stock-based compensation expense Depreciation and amortization expense Interest and other expense (income), net Provision (benefit) for income taxes Restructuring charges Adjusted EBITDA Mar 31, 2018 $60,997 73,266 96,846 11,043 2,885 (983) $244,054 Reconciliation of GAAP Net Income to Adjusted EBITDA Jun 30, 2018 $100,117 79,469 105,982 13,757 (34,250) (265) Three months ended $264,810 Sep 30, 2018 $789,179 91,606 111,947 4,610 (701,921) (18) $295,403 Dec 31, 2018 $255,303 81,887 110,723 371 (48,766) (2,989) $396,529 Mar 31, 2019 $190,804 83,491 113,474 (2,845) (94,301) $290,623 Note: Adjusted EBITDA is defined as GAAP net income adjusted to exclude stock-based compensation expense, depreciation and amortization expense, interest and other expense, net, provision (benefit) for income taxes, restructuring charges and one-time nonrecurring gain.#12GAAP to Non-GAAP Reconciliations ($, thousands) Cost of revenue Research and development Sales and marketing General and administrative Cost of revenue Research and development Sales and marketing General and administrative GAAP $264,011 146,246 205,799 77,176 GAAP $222,823 123,346 178,059 65,718 Three months ended Mar 31, 2019 Stock-based compensation expense $5,048 46,261 18,065 14,117 Stock-based compensation expense Three months ended Mar 31, 2018 $4,799 41,946 14,822 Amortization of acquired intangible assets 11,699 $4,320 465 Amortization of acquired intangible assets $4,477 465 I Restructuring charges Restructuring charges ($60) (330) (400) (193) Non-GAAP $254,643 99,985 187,269 63,059 Non-GAAP $213,607 81,730 163,172 54,212#13@TwitterlR