“…To analyze ongoing conversations that construct organizational legitimacy (Schultz et al, 2013), we selected those tweets that included a hashtag (e.g., #italybank or #statehelp). Furthermore, we excluded all tweets Martin & Boynton, 2005) Statistical software for data management and statistical analysis, such as RATE (e.g., Singh, Tucker, & House, 1986) Statistical software for data management and quantitative analysis, such as SPSS, SPSS, STATA, SAS, or R (e.g., MacMillan, Money, Downing, & Hillenbrand, 2005) Software based on programming languages, such as Python, that are able to process huge amounts of data (e.g., Castelló et al, 2016) Unit of analysis News media article (e.g., Deephouse & Carter, 2005) Reports, rankings, ratings, institutional linkages (e.g., Baum & Oliver, 1991) Survey items covering an organizational aspect (e.g., Helm, 2007) Comments, such as tweets, Facebook posts, blog posts, and so on (e.g., Castelló et al, 2016 ordinal variables, such as qualification of adjectives, "good environmental actions", "bad environmental actions" (e.g., Brown & Deegan, 1998) Binary variable about absence or presence of regulator's actions, accreditation, collaborative relations or registration of licenses (e.g., Ruef & Scott, 1998); ordinal variable (e.g., Deephouse & Carter, 2005) Ordinal variable, typically Likert-type scale for various items representing organizational aspects/ dimensions (e.g., Fombrun, 2007); from three (Highhouse et al 2009) to 51 items (Davies, Chun, Da Silva, & Roper, 2003) Scale variable with the sentiment score that variate...…”