Rebecca Lange

This paper reports on a study that is part of a project which aims to develop a multimodal analytical approach for big data analytics, initially in the context of violent extremism. The findings reported here tested the application of natural language processing models to the text of a sample of articles from the online magazines Dabiq and Rumiyah, produced by the Islamic extremist organisation ISIS. For comparison, text of articles found by reverse image search software which re-used the lead images from the original articles in text which either reported on or opposed extremist activities was also analysed. The aim was to explore what insights the natural language processing models could provide to distinguish between texts produced as propaganda to incite violent extremism and texts which either reported on or opposed violent extremism. The results showed that some valuable insights can be gained from such an approach and that these results could be improved through integrating automated analyses with a theoretical approach with analysed language and images in their immediate and social contexts. Such an approach will inform the interpretation of results and will be used in training software so that stronger results can be achieved in the future.

This study takes a systemic functional multimodal social semiotic approach to the analysis and discussion of image and text relations in two sets of data. First, patterns of contextualisation of images and text in the online magazines Dabiq and Rumiyah produced by the Islamic extremist organisation which refers to itself as Islamic State (referred to here as ISIS) are examined. The second data set consists of a sample of texts from Western online news and blog sites which include recontextualisations of images found in the first data set. A sample of examples of the use and re-use of images is discussed in order to identify patterns of similarity and difference when images and text are recontextualised. It is argued that the ISIS material tends to foreground the interpersonal metafunction in combination with the textual metafunction (i.e. the stance towards the content and the organisation of the message for this purpose), while the other data set tends to foreground the ideational metafunction (the participants, processes and circumstances of what is being reported). These inferences indicate that further exploration of a larger data set is worth pursuing. Such studies would provide deeper insights helping to distinguish between online material which supports terrorism and that which opposes it, as well as facilitating the further development of multimodal social semiotic approaches to image and text relations.

We build on a recent photometric decomposition analysis of 7506 Galaxy and Mass Assembly (GAMA) survey galaxies to derive stellar mass function fits to individual spheroid and disc component populations down to a lower mass limit of log(M_*/M_⊙) = 8. We find that the spheroid/disc mass distributions for individual galaxy morphological types are well described by single Schechter function forms. We derive estimates of the total stellar mass densities in spheroids (ρ_spheroid = 1.24 ± 0.49 × 10⁸ M_⊙ Mpc ⁻³h_0.7) and discs (ρ_disc = 1.20 ± 0.45 × 10⁸ M_⊙ Mpc ⁻³h_0.7), which translates to approximately 50 per cent of the local stellar mass density in spheroids and 48 per cent in discs. The remaining stellar mass is found in the dwarf ‘little blue spheroid’ class, which is not obviously similar in structure to either classical spheroid or disc populations. We also examine the variation of component mass ratios across galaxy mass and group halo mass regimes, finding the transition from spheroid to disc mass dominance occurs near galaxy stellar mass ∼10¹¹ M_⊙ and group halo mass ∼10^12.5 M_⊙h⁻¹. We further quantify the variation in spheroid-to-total mass ratio with group halo mass for central and satellite populations as well as the radial variation of this ratio within groups.

We present the Lambda Adaptive Multi-Band Deblending Algorithm in R (lambdar), a novel code for calculating matched aperture photometry across images that are neither pixel- nor PSF-matched, using prior aperture definitions derived from high-resolution optical imaging. The development of this program is motivated by the desire for consistent photometry and uncertainties across large ranges of photometric imaging, for use in calculating spectral energy distributions. We describe the program, specifically key features required for robust determination of panchromatic photometry: propagation of apertures to images with arbitrary resolution, local background estimation, aperture normalization, uncertainty determination and propagation, and object deblending. Using simulated images, we demonstrate that the program is able to recover accurate photometric measurements in both high-resolution, low-confusion, and low-resolution, high-confusion, regimes. We apply the program to the 21-band photometric data set from the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR; Driver et al. 2016), which contains imaging spanning the far-UV to the far-IR. We compare photometry derived from lambdar with that presented in Driver et al. (2016), finding broad agreement between the data sets. None the less, we demonstrate that the photometry from lambdar is superior to that from the GAMA PDR, as determined by a reduction in the outlier rate and intrinsic scatter of colours in the lambdar data set. We similarly find a decrease in the outlier rate of stellar masses and star formation rates using lambdar photometry. Finally, we note an exceptional increase in the number of UV and mid-IR sources able to be constrained, which is accompanied by a significant increase in the mid-IR colour–colour parameter-space able to be explored.

We report an expanded sample of visual morphological classifications from the Galaxy and Mass Assembly survey phase two, which now includes 7556 objects (previously 3727 in phase one). We define a local (z < 0.06) sample and classify galaxies into E, S0-Sa, SB0-SBa, Sab-Scd, SBab-SBcd, Sd-Irr, and ‘little blue spheroid’ types. Using these updated classifications, we derive stellar mass function fits to individual galaxy populations divided both by morphological class and more general spheroid- or disc-dominated categories with a lower mass limit of log(M_*/M_⊙) = 8 (one dex below earlier morphological mass function determinations). We find that all individual morphological classes and the combined spheroid-/bulge-dominated classes are well described by single Schechter stellar mass function forms. We find that the total stellar mass densities for individual galaxy populations and for the entire galaxy population are bounded within our stellar mass limits and derive an estimated total stellar mass density of ρ_* = 2.5 × 10⁸ M_⊙ Mpc⁻³ h_0.7, which corresponds to an approximately 4 per cent fraction of baryons found in stars. The mass contributions to this total stellar mass density by galaxies that are dominated by spheroidal components (E and S0-Sa classes) and by disc components (Sab-Scd and Sd-Irr classes) are approximately 70 and 30 per cent, respectively.

Line-of-sight velocities of gas and stars can constrain dark matter (DM) within rotationally supported galaxies if they trace circular orbits extensively. Photometric asymmetries may signify non-circular motions, requiring spectra with dense spatial coverage. Our integral-field spectroscopy of 178 galaxies spanned the mass range of the Sydney-AAO Multi-object integral field spectrograph (SAMI) Galaxy Survey. We derived circular speed curves (CSCs) of gas and stars from non-parametric fits out to r ∼ 2r_e. For 12/14 with measured H i profiles, ionized gas and H i maximum velocities agreed. We fitted mass-follows-light models to 163 galaxies by approximating the radial light profile as nested, very flattened mass homeoids viewed as a Sérsic form. Fitting broad-band spectral energy distributions to Sloan Digital Sky Survey images gave median stellar mass/light 1.7 assuming a Kroupa initial mass function (IMF) versus 2.6 dynamically. Two-thirds of the dynamical mass/light measures were consistent with star+remnant IMFs. One-fifth required upscaled starlight to fit, hence comparable mass of unobserved baryons and/or DM distributed like starlight across the SAMI aperture that came to dominate motions as the starlight CSCs declined rapidly. The rest had mass distributed differently from light. Subtracting fits of Sérsic radial profiles to 13 VIKING Z-band images revealed residual weak bars. Near the bar major axis, we assessed m = 2 streaming velocities, and found deviations usually −1 from the CSC; three showed no deviation. Thus, asymmetries rarely influenced the CSC despite colocated shock-indicating, emission-line flux ratios in more than 2/3 of our sample.

We present the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR) constituting over 230 deg² of imaging with photometry in 21 bands extending from the far-UV to the far-IR. These data complement our spectroscopic campaign of over 300k galaxies, and are compiled from observations with a variety of facilities including: GALaxy Evolution eXplorer, Sloan Digital Sky Survey, Visible and Infrared Telescope for Astronomy (VISTA), Wide-field Infrared Survey Explorer, and Herschel, with the GAMA regions currently being surveyed by VLT Survey Telescope (VST) and scheduled for observations by Australian Square Kilometer Array Pathfinder (ASKAP). These data are processed to a common astrometric solution, from which photometry is derived for ∼221 373 galaxies with r < 19.8 mag. Online tools are provided to access and download data cutouts, or the full mosaics of the GAMA regions in each band. We focus, in particular, on the reduction and analysis of the VISTA VIsta Kilo-degree INfrared Galaxy data, and compare to earlier data sets (i.e. 2MASS and UKIDSS) before combining the data and examining its integrity. Having derived the 21-band photometric catalogue, we proceed to fit the data using the energy balance code magphys. These measurements are then used to obtain the first fully empirical measurement of the 0.1–500 μm energy output of the Universe. Exploring the cosmic spectral energy distribution across three time-intervals (0.3–1.1, 1.1–1.8, and 1.8–2.4 Gyr), we find that the Universe is currently generating (1.5 ± 0.3) × 10³⁵ h₇₀ W Mpc⁻³, down from (2.5 ± 0.2) × 10³⁵ h₇₀ W Mpc⁻³ 2.3 Gyr ago. More importantly, we identify significant and smooth evolution in the integrated photon escape fraction at all wavelengths, with the UV escape fraction increasing from 27(18) per cent at z = 0.18 in NUV(FUV) to 34(23) per cent at z = 0.06. The GAMA PDR can be found at: http://gama-psi.icrar.org/.