Erkut Altındağ

This article reads the Billboard Hot 100 as a barometer of American cultural life and asks how the Schumpeterian process of creative destruction has reshaped the popular‐music chart across nearly seven decades. Drawing on the complete weekly chart from 1958 to 2026, comprising 353,800 song‐week observations, it measures creative destruction through how many new songs enter the chart, how long they stay, how unequally chart space is shared, and how high new songs debut. Data‐driven change‐point analysis locates a stable break at the end of the 1970s and a second, more specification‐dependent break in the late 2000s, and the article uses 1978 and 2008 as reporting boundaries for three regimes, each anchored in a recognizable moment of American musical life. The singles regime, which closed with the soundtrack‐driven disco boom, combined rapid but widely distributed turnover; the album and catalog regime of the MTV and compact‐disc decades froze the chart into a slow‐moving inventory of long‐lived hits; and the streaming and platform regime restored rapid turnover while pushing concentration to historic highs. Survival analysis reveals a newly bimodal mortality in which nearly half of the songs entering the chart in the streaming era vanish within 2 weeks while a small set of survivors endures longer than ever. The chart thus models a volatile oligopoly that mirrors broader American anxieties about acceleration, disposability, and inequality, and it records a shift from a broad middle of shared, moderately durable hits toward a narrow canon of dominant works surrounded by rapid churn.

Internet memes have become a central mode of cultural expression and political discourse in digital environments, particularly among younger users who have come of age in platform-mediated communic...

Drawing on the knowledge-based view, dynamic capabilities theory, and network embeddedness perspectives, this study examines how technological portfolio diversity and cross-border collaboration shape the growth of national software ecosystems. We construct a quarterly panel of 170 economies over 24 quarters (2020 to 2026) from the GitHub Innovation Graph, an openly licensed big data source covering developer populations, repository stocks, programming language portfolios, and 82,000 dyadic cross-border collaboration observations. Two-way fixed effects estimations with clustered standard errors reveal that within-economy increases in programming language portfolio entropy significantly predict subsequent developer ecosystem growth, whereas curvilinear, moderation, and within-economy network embeddedness effects are not supported. Between-economy comparisons show that highly embedded ecosystems grow more slowly, consistent with convergence dynamics in the global software economy. The findings position technological diversification as a strategic capability operating at the ecosystem level and demonstrate that structural network position, although highly persistent, does not translate into short-run growth advantages. Implications for software strategy, information systems research, and technology policy are discussed.

While Instagram’s visual ecology provides unique affordances for contemporary social movements, it is essential to understand #BlackLivesMatter within its broader sociopolitical and discursive cont...